Prediction of an accurate wind speed of wind farms is necessary because of the intermittent nature
of wind for any region. Number of methods such as persistence, physical, statistical, spatial correlation, artificial
intelligence network and hybrid are generally available for prediction of wind speed. In this paper, ANN based
methods viz., Multi Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are used. The
performance of the networks applied for prediction of wind speed is evaluated by model performance indicators
viz., Correlation Coefficient (CC), Model Efficiency (MEF) and Mean Absolute Percentage Error (MAPE).
Meteorological parameters such as maximum and minimum temperature, air pressure, solar radiation and
altitude are considered as input units for MLP and RBF networks to predict the extreme wind speed at Delhi.
The study shows the values of CC, MEF and MAPE between the observed and predicted wind speed (using
MLP) are computed as 0.992, 95.4% and 4.3% respectively while training the network data. For RBF network,
the values of CC, MEF and MAPE are computed as 0.992, 95.9% and 3.0% respectively. The model
performance analysis indicates the RBF is better suited network among two different networks studied for
prediction of extreme wind speed at Delhi.
The accurate prediction of solar irradiation has been
a leading problem for better energy scheduling approach.
Hence in this paper, an Artificial neural network based solar
irradiance is proposed for five days duration the data is
obtained from National Renewable Energy Laboratory, USA
and the simulation were performed using MATLAB 2013. It
was found that the neural model was able to predict the solar
irradiance with a mean square error of 0.0355.
An Ant colony optimization algorithm to solve the broken link problem in wire...IJERA Editor
Aco is a well –known metahuristic in which a colony of artificial ants cooperates in explain Good solution to a combinational optimization problem. Wireless sensor consisting of nodes with limited power is deployed to gather useful information From the field. In wireless sensor network it is critical to collect the information in an energy efficient Manner.ant colony optimization, a swarm intelligence based optimization technique, is widely used In network routing. A novel routing approach using an ant colony optimization algorithm is proposed for wireless sensor Network consisting of stable nodes illustrative example details description and cooperative performance test result the proposed approach are included. The approach is also implementing to a small sized hardware component as a router chip simulation result show that proposed algorithm Provides promising solution allowing node designers to efficiency operate routing tasks.
Address-light and energy aware routing protocol for wireless sensor networkTELKOMNIKA JOURNAL
In recent years, sensor networks applications were used in many criteria. Because of its vast applications, so many researchers studied these networks. Wireless sensor networks contain significant number of sensor nodes; they are suitable medium for collecting and sending data or informing the sink about an event. This study presents a new integrated method for routing in sensor networks which is based on remaining energy of the nodes and existing space between each node and the sink. This method is more suitable for large and medium volume of data. Lifetime enhancement of the network is the main purpose of this method which is obtained by fair division of nodes roles in transmission of data to the sink. In ALERP algorithm (Address Light, Label-Based and Energy-Aware Routing Protocol), in order to reduce network overload and energy consuming as well as enhancement of network lifetime, we used predetermined routes as well as routing based on packet labels. Energy consumption in the entire network is another advantage of this method. The existence of various parameters on this algorithm will lead to more flexibility of it. Generally, conducted simulations indicate higher uniformity in energy consumption of nodes.
DATA GATHERING ALGORITHMS FOR WIRELESS SENSOR NETWORKS: A SURVEYijasuc
Recent developments in processor, memory and radio technology have enabled wireless sensor networks
which are deployed to collect useful information from an area of interest. The sensed data must be
gathered and transmitted to a base station where it is further processed for end-user queries. Since the
network consists of low-cost nodes with limited battery power, power efficient methods must be employed
for data gathering and aggregation in order to achieve long network lifetimes. In an environment where in
a round of communication each of the sensor nodes has data to send to a base station, it is important to
minimize the total energy consumed by the system in a round so that the system lifetime is maximized. With
the use of data fusion and aggregation techniques, while minimizing the total energy per round, if power
consumption per node can be balanced as well, a near optimal data gathering and routing scheme can be
achieved in terms of network lifetime. Several application specific sensor network data gathering protocols
have been proposed in research literatures. However, most of the proposed algorithms have been some
attention to the related network lifetime and saving energy are two critical issues for wireless sensor
networks. In this paper we have explored general network lifetime in wireless sensor networks and made an
extensive study to categorize available data gathering techniques and analyze possible network lifetime on
them.
The accurate prediction of solar irradiation has been
a leading problem for better energy scheduling approach.
Hence in this paper, an Artificial neural network based solar
irradiance is proposed for five days duration the data is
obtained from National Renewable Energy Laboratory, USA
and the simulation were performed using MATLAB 2013. It
was found that the neural model was able to predict the solar
irradiance with a mean square error of 0.0355.
An Ant colony optimization algorithm to solve the broken link problem in wire...IJERA Editor
Aco is a well –known metahuristic in which a colony of artificial ants cooperates in explain Good solution to a combinational optimization problem. Wireless sensor consisting of nodes with limited power is deployed to gather useful information From the field. In wireless sensor network it is critical to collect the information in an energy efficient Manner.ant colony optimization, a swarm intelligence based optimization technique, is widely used In network routing. A novel routing approach using an ant colony optimization algorithm is proposed for wireless sensor Network consisting of stable nodes illustrative example details description and cooperative performance test result the proposed approach are included. The approach is also implementing to a small sized hardware component as a router chip simulation result show that proposed algorithm Provides promising solution allowing node designers to efficiency operate routing tasks.
Address-light and energy aware routing protocol for wireless sensor networkTELKOMNIKA JOURNAL
In recent years, sensor networks applications were used in many criteria. Because of its vast applications, so many researchers studied these networks. Wireless sensor networks contain significant number of sensor nodes; they are suitable medium for collecting and sending data or informing the sink about an event. This study presents a new integrated method for routing in sensor networks which is based on remaining energy of the nodes and existing space between each node and the sink. This method is more suitable for large and medium volume of data. Lifetime enhancement of the network is the main purpose of this method which is obtained by fair division of nodes roles in transmission of data to the sink. In ALERP algorithm (Address Light, Label-Based and Energy-Aware Routing Protocol), in order to reduce network overload and energy consuming as well as enhancement of network lifetime, we used predetermined routes as well as routing based on packet labels. Energy consumption in the entire network is another advantage of this method. The existence of various parameters on this algorithm will lead to more flexibility of it. Generally, conducted simulations indicate higher uniformity in energy consumption of nodes.
DATA GATHERING ALGORITHMS FOR WIRELESS SENSOR NETWORKS: A SURVEYijasuc
Recent developments in processor, memory and radio technology have enabled wireless sensor networks
which are deployed to collect useful information from an area of interest. The sensed data must be
gathered and transmitted to a base station where it is further processed for end-user queries. Since the
network consists of low-cost nodes with limited battery power, power efficient methods must be employed
for data gathering and aggregation in order to achieve long network lifetimes. In an environment where in
a round of communication each of the sensor nodes has data to send to a base station, it is important to
minimize the total energy consumed by the system in a round so that the system lifetime is maximized. With
the use of data fusion and aggregation techniques, while minimizing the total energy per round, if power
consumption per node can be balanced as well, a near optimal data gathering and routing scheme can be
achieved in terms of network lifetime. Several application specific sensor network data gathering protocols
have been proposed in research literatures. However, most of the proposed algorithms have been some
attention to the related network lifetime and saving energy are two critical issues for wireless sensor
networks. In this paper we have explored general network lifetime in wireless sensor networks and made an
extensive study to categorize available data gathering techniques and analyze possible network lifetime on
them.
Opportunistic routing algorithm for relay node selection in wireless sensor n...LogicMindtech Nologies
NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
ENERGY CONSUMPTION IMPROVEMENT OF TRADITIONAL CLUSTERING METHOD IN WIRELESS S...IJCNCJournal
In the traditional clustering routing protocol of wireless sensor network, LEACH protocol (Low Energy
Adaptive Clustering Hierarchy) is considered to have many outstanding advantages in the implementation
of the hierarchy according to low energy adaptive cluster to collect and distribute the data to the base
station. The main objective of LEACH is: To prolong life time of the network, reduce the energy
consumption by each node, using the data concentration to reduce bulletins in the network. However, in the
case of large network, the distance from the nodes to the base station is very different. Therefore, the
energy consumption when becoming the host node is very different but LEACH is not based on the
remaining energy to choose the host node, which is based on the number of times to become the host node
in the previous rounds. This makes the nodes far away from the base station lose power sooner.
In this paper, we give a new routing protocol based on the LEACH protocol in order to improve operating
time of sensor network by considering energy issues and distance in selecting the cluster-head (CH), at that
time the nodes with high energy and near the base station (BS) will have a greater probability of becoming
the cluster-head than the those in far and with lower energy.
SENSOR SELECTION SCHEME IN WIRELESS SENSOR NETWORKS: A NEW ROUTING APPROACHcsandit
In this paper, we propose a novel energy efficient environment monitoring scheme for wireless
sensor networks, based on data mining formulation. The proposed adapting routing scheme for
sensors for achieving energy efficiency. The experimental validation of the proposed approach
using publicly available Intel Berkeley lab Wireless Sensor Network dataset shows that it is
possible to achieve energy efficient environment monitoring for wireless sensor networks, with a
trade-off between accuracy and life time extension factor of sensors, using the proposed
approach.
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
An improved ant colony optimization algorithm for wire optimizationjournalBEEI
Wire optimization has become one of the greatest challenges in today’s circuit design. This paper presents a method for wire optimization in circuit routing using an improved ant colony optimization with Steiner nodes (ACOSN) algorithm. Circuit delay and power dissipation are primarily affected by the length of the routed wire. Thus, the main goal of this proposed algorithm is to find the shortest route from one point to another using an algorithm that relies on the artificial behavior of ants. The algorithm is implemented in the JAVA programming language. The proposed ACOSN algorithm is compared with the conventional ant colony optimization (ACO) algorithm in terms of efficiency and routing performance when applied to three types of circuits: emitter-coupled logic, 741 output and a cascode amplifier. The performance of the proposed method is analyzed based on circuit information such as total wire routing, total number of nets, total wire reduction, terminals per net and total terminals. From the simulation analysis, it is shown that the proposed ACOSN algorithm gives the most benefit to complex circuits, where it successfully reduces the wire length by 21.52% for a cascode amplifier circuit, 14.49% for a 741 output circuit, and 10.43% for emitter-coupled logic circuit.
Support Vector Machine for Wind Speed PredictionIJRST Journal
The energy is a vital input for the social and economic development of any nation. With increasing agricultural and industrial activities in the country, the demand for energy is also increasing. The increasing use of natural and renewable energy sources is needed to take the burden of our current dependency on fossil fuels. Development and analysis of renewable energy models helps utility in energy forecasting, planning, research and policy making. The wind power is a clean, inexhaustible, and almost a free source of energy. But the integration of wind parks with the power grid has resulted in many challenges for the utility in terms of commitment and control of power plants. As wind speed and wind direction fluctuate frequently, the accurate long-term and short-term forecasting of wind speed is important for ascertaining the wind power generation availability. To deal with wind speed forecasting, many methods have been developed such as physical method, which use lots of physical considerations to reach the best forecasting precision and other is the statistical method, which specializes in finding the relationship of the measured power data. Wind speed can be predicted by using time series analysis, artificial neural network, Kalman Filter method, linear prediction method, spatial correlation models and wavelet, also by using the support vector machines. In this paper, the SVM is used for day ahead prediction of wind speed using historical data of wind park. In this paper Support Vector Machine (SVM) results are compared with feedforward Backpropagation neural network. It is observed that the Mean Absolute Percentage Error (MAPE) by SVM method is around 7% and correlation coefficient is close to 1. This justifies the ability of SVM for wind speed prediction task than Backpropagation algorithm.
SENSOR SELECTION SCHEME IN TEMPERATURE WIRELESS SENSOR NETWORKijwmn
In this paper, we propose a novel energy efficient environment monitoring scheme for wireless sensor
networks, based on data mining formulation. The proposed adapting routing scheme for sensors for
achieving energy efficiency from temperature wireless sensor network data set. The experimental
validation of the proposed approach using publicly available Intel Berkeley lab Wireless Sensor Network
dataset shows that it is possible to achieve energy efficient environment monitoring for wireless sensor
networks, with a trade-off between accuracy and life time extension factor of sensors, using the proposed
approach.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
Dear Student,
DREAMWEB TECHNO SOLUTIONS is one of the Hardware Training and Software Development centre available in
Trichy. Pioneer in corporate training, DREAMWEB TECHNO SOLUTIONS provides training in all software
development and IT-related courses, such as Embedded Systems, VLSI, MATLAB, JAVA, J2EE, CIVIL,
Power Electronics, and Power Systems. It’s certified and experienced faculty members have the
competence to train students, provide consultancy to organizations, and develop strategic
solutions for clients by integrating existing and emerging technologies.
ADD: No:73/5, 3rd Floor, Sri Kamatchi Complex, Opp City Hospital, Salai Road, Trichy-18
Contact @ 7200021403/04
phone: 0431-4050403
Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Netw...IJECEIAES
Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on KMeans clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity
Abstract In optical circuit switching the high values of blocking probability is resolved by dynamic wavelength routing algorithms with wavelength conversion. The aim of this paper is to study these algorithms. Then the algorithm is selected which gives good results with and without wavelength conversion. The selected algorithm is then checked for other parameters of networking namely throughput, packet delivery ratio, and delay. A comparative study is then carried out for increasing traffic. We try to prove that these algorithms satisfy the criteria of QoS parameters by this comparative study. The results of simulation show that the parameters follow the trend of blocking probability of the selected algorithm. Keywords: optical burst switching, throughput, packet delivery ratio, delay.
A Comparative study on Different ANN Techniques in Wind Speed Forecasting for...IOSRJEEE
There are several available renewable sources of energy, among which Wind Power is the one which is most uncertain in nature. This is because wind speed changes continuously with time leading to uncertainty in availability of amount of wind power generated. Hence, a short-term forecasting of wind speed will help in prior estimation of wind power generation availability for the grid and economic load dispatch.This paper present a comparative study of a Wind speed forecasting model using Artificial Neural Networks (ANN) with three different learning algorithms. ANN is used because it is a non-linear data driven, adaptive and very powerful tool for forecasting purposes. Here an attempt is made to forecast Wind Speed using ANN with Levenberg-Marquard (LM) algorithm, Scaled Conjugate Gradient (SCG) algorithm and Bayesian Regularization (BR) algorithm and their results are compared based on their convergence speed in training period and their performance in testing period on the basis of Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE).A 48 hour ahead wind speed is forecasted in this work and it is compared with the measured values using all three algorithms and the best out of the three is selected based on minimum error.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered as the main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance, which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Opportunistic routing algorithm for relay node selection in wireless sensor n...LogicMindtech Nologies
NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
ENERGY CONSUMPTION IMPROVEMENT OF TRADITIONAL CLUSTERING METHOD IN WIRELESS S...IJCNCJournal
In the traditional clustering routing protocol of wireless sensor network, LEACH protocol (Low Energy
Adaptive Clustering Hierarchy) is considered to have many outstanding advantages in the implementation
of the hierarchy according to low energy adaptive cluster to collect and distribute the data to the base
station. The main objective of LEACH is: To prolong life time of the network, reduce the energy
consumption by each node, using the data concentration to reduce bulletins in the network. However, in the
case of large network, the distance from the nodes to the base station is very different. Therefore, the
energy consumption when becoming the host node is very different but LEACH is not based on the
remaining energy to choose the host node, which is based on the number of times to become the host node
in the previous rounds. This makes the nodes far away from the base station lose power sooner.
In this paper, we give a new routing protocol based on the LEACH protocol in order to improve operating
time of sensor network by considering energy issues and distance in selecting the cluster-head (CH), at that
time the nodes with high energy and near the base station (BS) will have a greater probability of becoming
the cluster-head than the those in far and with lower energy.
SENSOR SELECTION SCHEME IN WIRELESS SENSOR NETWORKS: A NEW ROUTING APPROACHcsandit
In this paper, we propose a novel energy efficient environment monitoring scheme for wireless
sensor networks, based on data mining formulation. The proposed adapting routing scheme for
sensors for achieving energy efficiency. The experimental validation of the proposed approach
using publicly available Intel Berkeley lab Wireless Sensor Network dataset shows that it is
possible to achieve energy efficient environment monitoring for wireless sensor networks, with a
trade-off between accuracy and life time extension factor of sensors, using the proposed
approach.
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
An improved ant colony optimization algorithm for wire optimizationjournalBEEI
Wire optimization has become one of the greatest challenges in today’s circuit design. This paper presents a method for wire optimization in circuit routing using an improved ant colony optimization with Steiner nodes (ACOSN) algorithm. Circuit delay and power dissipation are primarily affected by the length of the routed wire. Thus, the main goal of this proposed algorithm is to find the shortest route from one point to another using an algorithm that relies on the artificial behavior of ants. The algorithm is implemented in the JAVA programming language. The proposed ACOSN algorithm is compared with the conventional ant colony optimization (ACO) algorithm in terms of efficiency and routing performance when applied to three types of circuits: emitter-coupled logic, 741 output and a cascode amplifier. The performance of the proposed method is analyzed based on circuit information such as total wire routing, total number of nets, total wire reduction, terminals per net and total terminals. From the simulation analysis, it is shown that the proposed ACOSN algorithm gives the most benefit to complex circuits, where it successfully reduces the wire length by 21.52% for a cascode amplifier circuit, 14.49% for a 741 output circuit, and 10.43% for emitter-coupled logic circuit.
Support Vector Machine for Wind Speed PredictionIJRST Journal
The energy is a vital input for the social and economic development of any nation. With increasing agricultural and industrial activities in the country, the demand for energy is also increasing. The increasing use of natural and renewable energy sources is needed to take the burden of our current dependency on fossil fuels. Development and analysis of renewable energy models helps utility in energy forecasting, planning, research and policy making. The wind power is a clean, inexhaustible, and almost a free source of energy. But the integration of wind parks with the power grid has resulted in many challenges for the utility in terms of commitment and control of power plants. As wind speed and wind direction fluctuate frequently, the accurate long-term and short-term forecasting of wind speed is important for ascertaining the wind power generation availability. To deal with wind speed forecasting, many methods have been developed such as physical method, which use lots of physical considerations to reach the best forecasting precision and other is the statistical method, which specializes in finding the relationship of the measured power data. Wind speed can be predicted by using time series analysis, artificial neural network, Kalman Filter method, linear prediction method, spatial correlation models and wavelet, also by using the support vector machines. In this paper, the SVM is used for day ahead prediction of wind speed using historical data of wind park. In this paper Support Vector Machine (SVM) results are compared with feedforward Backpropagation neural network. It is observed that the Mean Absolute Percentage Error (MAPE) by SVM method is around 7% and correlation coefficient is close to 1. This justifies the ability of SVM for wind speed prediction task than Backpropagation algorithm.
SENSOR SELECTION SCHEME IN TEMPERATURE WIRELESS SENSOR NETWORKijwmn
In this paper, we propose a novel energy efficient environment monitoring scheme for wireless sensor
networks, based on data mining formulation. The proposed adapting routing scheme for sensors for
achieving energy efficiency from temperature wireless sensor network data set. The experimental
validation of the proposed approach using publicly available Intel Berkeley lab Wireless Sensor Network
dataset shows that it is possible to achieve energy efficient environment monitoring for wireless sensor
networks, with a trade-off between accuracy and life time extension factor of sensors, using the proposed
approach.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
Dear Student,
DREAMWEB TECHNO SOLUTIONS is one of the Hardware Training and Software Development centre available in
Trichy. Pioneer in corporate training, DREAMWEB TECHNO SOLUTIONS provides training in all software
development and IT-related courses, such as Embedded Systems, VLSI, MATLAB, JAVA, J2EE, CIVIL,
Power Electronics, and Power Systems. It’s certified and experienced faculty members have the
competence to train students, provide consultancy to organizations, and develop strategic
solutions for clients by integrating existing and emerging technologies.
ADD: No:73/5, 3rd Floor, Sri Kamatchi Complex, Opp City Hospital, Salai Road, Trichy-18
Contact @ 7200021403/04
phone: 0431-4050403
Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Netw...IJECEIAES
Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on KMeans clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity
Abstract In optical circuit switching the high values of blocking probability is resolved by dynamic wavelength routing algorithms with wavelength conversion. The aim of this paper is to study these algorithms. Then the algorithm is selected which gives good results with and without wavelength conversion. The selected algorithm is then checked for other parameters of networking namely throughput, packet delivery ratio, and delay. A comparative study is then carried out for increasing traffic. We try to prove that these algorithms satisfy the criteria of QoS parameters by this comparative study. The results of simulation show that the parameters follow the trend of blocking probability of the selected algorithm. Keywords: optical burst switching, throughput, packet delivery ratio, delay.
A Comparative study on Different ANN Techniques in Wind Speed Forecasting for...IOSRJEEE
There are several available renewable sources of energy, among which Wind Power is the one which is most uncertain in nature. This is because wind speed changes continuously with time leading to uncertainty in availability of amount of wind power generated. Hence, a short-term forecasting of wind speed will help in prior estimation of wind power generation availability for the grid and economic load dispatch.This paper present a comparative study of a Wind speed forecasting model using Artificial Neural Networks (ANN) with three different learning algorithms. ANN is used because it is a non-linear data driven, adaptive and very powerful tool for forecasting purposes. Here an attempt is made to forecast Wind Speed using ANN with Levenberg-Marquard (LM) algorithm, Scaled Conjugate Gradient (SCG) algorithm and Bayesian Regularization (BR) algorithm and their results are compared based on their convergence speed in training period and their performance in testing period on the basis of Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE).A 48 hour ahead wind speed is forecasted in this work and it is compared with the measured values using all three algorithms and the best out of the three is selected based on minimum error.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered as the main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance, which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered asthe main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance,which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
EFFICIENCY ENHANCEMENT BASED ON ALLOCATING BIZARRE PEAKSijwmn
A new work has been proposed in this paper in order to overcome one of the main drawbacks that found in
the Orthogonal Frequency Division Multiplex (OFDM) systems, namely Peak to Average Power Ratio
(PAPR). Furthermore, this work will be compared with a previously published work that uses the neural
network (NN) as a solution to remedy this deficiency.
The proposed work could be considered as a special averaging technique (SAT), which consists of wavelet
transformation in its first stage, a globally statistical adaptive detecting algorithm as a second stage; and
in the third stage it replaces the affected peaks by making use of moving average filter process. In the NN
work, the learning process makes use of a previously published work that is based on three linear coding
techniques.
In order to check the proposed work validity, a MATLAB simulation has been run and has two main
variables to compare with; namely BER and CCDF curves. This is true under the same bandwidth
occupancy and channel characteristics. Two types of tested data have been used; randomly generated data
and a practical data that have been extracted from a funded project entitled by ECEM. From the achieved
simulation results, the work that is based on SAT shows promising results in reducing the PAPR effect
reached up to 80% over the work in the literature and our previously published work. This means that this
work gives an extra reduction up to 15% of our previously published work. However, this achievement will
be under the cost of complexity. This penalty could be optimized by imposing the NN to the SAT work in
order to enhance the wireless systems performance. Orthogonal Frequency Division Multiplexing
EFFICIENCY ENHANCEMENT BASED ON ALLOCATING BIZARRE PEAKSijwmn
A new work has been proposed in this paper in order to overcome one of the main drawbacks that found in
the Orthogonal Frequency Division Multiplex (OFDM) systems, namely Peak to Average Power Ratio
(PAPR). Furthermore, this work will be compared with a previously published work that uses the neural
network (NN) as a solution to remedy this deficiency.
The proposed work could be considered as a special averaging technique (SAT), which consists of wavelet
transformation in its first stage, a globally statistical adaptive detecting algorithm as a second stage; and
in the third stage it replaces the affected peaks by making use of moving average filter process. In the NN
work, the learning process makes use of a previously published work that is based on three linear coding
techniques.
In order to check the proposed work validity, a MATLAB simulation has been run and has two main
variables to compare with; namely BER and CCDF curves. This is true under the same bandwidth
occupancy and channel characteristics. Two types of tested data have been used; randomly generated data
and a practical data that have been extracted from a funded project entitled by ECEM. From the achieved
simulation results, the work that is based on SAT shows promising results in reducing the PAPR effect
reached up to 80% over the work in the literature and our previously published work. This means that this
work gives an extra reduction up to 15% of our previously published work. However, this achievement will
be under the cost of complexity. This penalty could be optimized by imposing the NN to the SAT work in
order to enhance the wireless systems performance.
WIND SPEED & POWER FORECASTING USING ARTIFICIAL NEURAL NETWORK (NARX) FOR NEW...Journal For Research
Continuous Depleting conventional fuel reserves and its impact as increasing global warming concerns have diverted world attention towards non-conventional energy sources. Out of different non-conventional energy sources wind energy can be consider as one of the cleanest source with minimum possible pollution or harmful emissions and has the potential to decrease the relying on conventional energy sources. Today Wind energy can play a vital role to meet our energy demands; however, it faces various issues such as intermittent nature and frequency instability. To reduce such issues the knowledge of futuristic weather conditions and wind speed trend are required. This work mainly describes the implementation of NARX Artificial neural network for wind speed & power forecasting with the help of historical data available from wind farms.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
Short Term Electrical Load Forecasting by Artificial Neural NetworkIJERA Editor
This paper presents an application of artificial neural networks for short-term times series electrical load
forecasting. An adaptive learning algorithm is derived from system stability to ensure the convergence of
training process. Historical data of hourly power load as well as hourly wind power generation are sourced from
European Open Power System Platform. The simulation demonstrates that errors steadily decrease in training
with the adaptive learning factor starting at different initial value and errors behave volatile with constant
learning factors with different values
IMPLEMENTING PACKET BROADCASTING ALGORITHM OF MIMO BASED MOBILE AD-HOC NETWOR...IJNSA Journal
With the rapid growth of wireless communication infras,,tructure over the recent few years, new challenges has been posed on the system and analysis on wireless adhoc networking. Implementation of MIMO communication in such type of network is enhancing the packet transmission capabilities. There are different techniques for cooperative transmission and broadcasting packet in MIMO equipped Mobile Adhoc Network. We have employed a model network in the OPNET environment and propose a new scheduling algorithm based on investigating the different broadcasting algorithm. The new broadcasting algorithm improves the packet transmission rate of the network based on energy performance of the network and minimizes the BER for different transmission mode which is illustrated in this paper. The simulations are done in MATLAB and OPNET environment and the simulated result for the packet transmission rate are collected and shown in the tabular form. Also simulate the network for generating a comparative statement for each mobile node. And performance analysis is also done for the model network. The main focus is to minimize BER and improve information efficiency of the network.
Implementing packet broadcasting algorithm of mimo based mobile ad hoc networ...IJNSA Journal
With the rapid growth of wireless communication infras,,tructure over the recent few years, new
challenges has been posed on the system and analysis on wireless adhoc networking. Implementation of
MIMO communication in such type of network is enhancing the packet transmission capabilities. There
are different techniques for cooperative transmission and broadcasting packet in MIMO equipped
Mobile Adhoc Network. We have employed a model network in the OPNET environment and propose a
new scheduling algorithm based on investigating the different broadcasting algorithm. The new
broadcasting algorithm improves the packet transmission rate of the network based on energy
performance of the network and minimizes the BER for different transmission mode which is illustrated
in this paper. The simulations are done in MATLAB and OPNET environment and the simulated result
for the packet transmission rate are collected and shown in the tabular form. Also simulate the network
for generating a comparative statement for each mobile node. And performance analysis is also done for
the model network. The main focus is to minimize BER and improve information efficiency of the
network.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Design of c slotted microstrip antenna using artificial neural network modeleSAT Journals
Abstract In this paper, neural network model has been used to estimation of resonance frequency of a coaxial feed C-slotted Microstrip Antenna. The Multi-Layer Perceptron Feed forward back Propagation (MLPFFBP) and Radial basis function Artificial Neural Network (RBFANN) have been used to implement the neural network model. A relative performance analysis of the proposed neural network for different training algorithms. Number of neurons and number of hidden layer is also carried out for estimating the resonance frequency. The method of moment (MOM) based IE3D software was used to generate data dictionary for training and validation set of ANN. The results obtain using ANN are compared with simulation feeding and found quite satisfactory and also it is concluded that RBFANN network is more accurate and fast compared to MLPFFBP network algorithm. Index Terms: Artificial Neural Network, C slot, Microstrip Antenna, Multilayer Feed Forward Networks, Radial basis function Artificial Neural Network, Resonance frequency.
Estimation of Weekly Reference Evapotranspiration using Linear Regression and...IDES Editor
The study investigates the applicability of linear
regression and ANN models for estimating weekly reference
evapotranspiration (ET0) at Tirupati, Nellore, Rajahmundry,
Anakapalli and Rajendranagar regions of Andhra Pradesh.
The climatic parameters influencing ET0 were identified
through multiple and partial correlation analysis. The
sunshine, temperature, wind velocity and relative humidity
mostly influenced the study area in the weekly ET0 estimation.
Linear regression models in terms of the climatic parameters
influencing the regions and, optimal neural network
architectures considering these climatic parameters as inputs
were developed. The models’ performance was evaluated with
respect to ET0 estimated by FAO-56 Penman-Monteith method.
The linear regression models showed a satisfactory
performance in the weekly ET0 estimation in the regions
selected for the present study. The ANN (4,4,1) models,
however, consistently showed a slightly improved performance
over linear regression models.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Scientific Management of Equipment in Medical Innovation LaboratoryScientific Review SR
Aim; To solve the problem of innovation laboratory instrument management and improve laboratory management level. Method; It is necessary to do an excellent job in managing innovative laboratory equipment by improving the equipment management system, functional division management, appointment registration, and strengthening the construction of management teams to guarantee the cultivation of innovation and entrepreneurship capabilities of undergraduates. Results; The number of innovative experimental projects approved and the number of project groups that the laboratory can accept at the same time was increased significantly. The utilization rate of laboratory equipment has increased, and the vacancy rate has decreased. Conclusion; Excellent instrument management can significantly improve the efficiency of scientific research in the innovation laboratory.
Internationalization and Sustainable Operations: A Broad Investigation of Chi...Scientific Review SR
We investigate if internationalization behaviors encourage sustainable operations of China’s manufacturing firms due to their substantial impact on climate change and special governance modes, and organize a heterogeneity test to clarify what kind of internationalization behaviors can robustly influence such operations. We find that firms with abundant assets and heavy-polluting feature are more committed to sustainable operations. Getting close to international sustainability standards, international auditing standards, and international business all improve sustainable operations. Heterogeneity test further shows that compared with international standards, the positive impact of international business on sustainable operation lacks a robustness, which responds to an argument that for one country, international business acts as a double-edged sword. Overall, this paper reveals internationalization as a key indicator significantly influencing economic, ecological, and social spheres in manufacturing sectors of emerging markets, and complying with well-accepted international standards can be significantly embodied in a more optimistic sustainable operations. However, how to deal with international business in a right manner is a research highlight worthy of ongoing discussion. We focus on different types of internationalization behaviors, and this indicator can theoretically inspire future study to dialectically evaluate the role of internationalization in addressing sustainability problems in emerging markets’ pillar industries.
Mechanical Engineering in Ancient Egypt, Part 92: Tomb Inscription During the...Scientific Review SR
This work is based on a previously published hypothesis which proposed that the solid matter of the universe can be represented as a vibrational wave of energy propagating over an ether or matrix through a mechanism that scrambles the degree of duality in matter: x% localized (solid), y% delocalized (wave). The main purpose of this paper is to present a two-dimensional approximation of the three-dimensional structure of the shape of the energy distribution of an atomic orbital to propose a mechanism through which the orbital can be transported as a vibration from a point A to point B in the matrix. This process requires cycles or oscillations of mounting-dismounting-remounting in which what travels from point A to point B is the energy forming the orbital and not the solid matter that it can form. The atomic seven-dimensional f orbital of hydrogen-like atoms is used as a model to show an analogy to the transformations that it can be submitted to when transported over the matrix.
Usability Engineering, Human Computer Interaction and Allied Sciences: With R...Scientific Review SR
Human Computer Interaction is actually responsible for the designing of the computing technologies keeping in mind the aspects of Interaction. Some of the fields viz. Man-Machine Interaction (MMI), User Experience Designing, User Experience Design, Human Centered Designing etc and importantly all these systems and technologies are dedicated to the designing of interface of various tools and systems such as computers, laptops, electronic systems, smart phones etc. Information Technology field is growing rapidly and there are various technologies are increasing viz. Big Data Management, Cloud Computing, Green Computing, Data Science, Internet of Things (IoT), HCI, Usability Engineering etc. Usability Engineering is gaining as a field of study as well and dedicated in creation of the higher usability and user friendliness of the electronic tools and products. In this field few aspects and technologies are most important and emerging viz. Human cognition, behavioral Research Methods, Quantitative techniques etc for the development of usability systems. Designing, implementation, usability even in multimedia material viz. audio-video may also practice in the Usability Engineering and allied fields. Wireframes including few other prototypes are required in maintaining of the better and healthy man and machine interaction. As the field is growing therefore, it is applicable in other sectors and allied areas and among these agriculture is important one. In agricultural sector different applications of information technologies are increasing and among this Usability Engineering and HCI are important one. In pre production and also in post production; directly and indirectly this technology is emerging and growing. This paper talks about the basics of this technologies and also its current and future technologies with reference to academic potentialities of this branch in Agricultural Informatics programs.
Concentration Distribution and Ecological Risk Assessment of Polycyclic Aroma...Scientific Review SR
The ecological risk assessment of 16 USEPA priority polycyclic aromatic hydrocarbon (PAHs) in water and sediments of Kolo creek, Niger Delta Nigeria was assessed the samples were collected from November, 2018 to June, 2019 from seven locations (A-G) along the creek. The samples were extracted using standard methods and analyzed using gas chromatography (model: HP5890 S). The concentrations of the PAHs in the water and sediment samples ranged between 0.000 - 9.239 µ/L and .002 – 374.35µg/Kg respectively. All the compounds analyzed were detected in all the sampling places, even area far from the flow stations. Hence, the urban runoffs, sewage discharges, and agricultural activities are implicated. Four rings hydrocarbon were present in higher concentration when compared to other PAHs in all sampling sites, with benz (a)anthracene having the highest values in both matrixes. Similarly, lower molecular weight (LMW) PAHs were present in lower concentrations in all sampling sites and they are known to exhibit higher lethal toxicity than the larger PAHs. HMW were present in high concentrations than LMW and are persistent in the environment as a result of their increase resistance to oxidation, reduction and vaporization as molecular weight increases. Similarly, The PAFs of the investigated creek is less than 5%, suggesting existences of minor ecological risks that are insignificance. However, the TEQs detected in high molecular weight showed that there is possibility of cancer to those who may be exposed to the bottom sediment. The indices measured in this habitat may put more pressures to the aquatic organisms and cause drastic changes to their ecosystem which may lead to species extinction.
Volume Fractions of Tantalum Carbides Deduced from the Ta Contents in the Mat...Scientific Review SR
Some superalloys for service at high temperature under stresses are strengthened by tantalum carbides. Their creep resistance depends on the quantity of TaC and this is the reason why it is often important to control the volume fraction of these carbides in the microstructure. Metallographic preparation followed by electron imaging and surface fraction measurements by image analysis is a frequent way for that. Another possibility is to deduce the mass fraction of TaC, and after their volume fraction, from the chemical composition of the matrix when the alloys are only double–phased, on the {matrix + TaC} type. In this work three alloys – chemically designed to be made exclusively of matrix and TaC – were elaborated and isothermally exposed to an elevated temperature for a duration long enough to allow the alloys being at their thermodynamic equilibria. The chemical compositions of the alloy and of its matrix were measured and the results allowed evaluating their TaC mass fractions which were converted in volume fractions. The obtained TaC fractions were compared to results issued from thermodynamic calculations. Good agreement was found for the three alloys, and this allowed to exploit the used software and thermodynamic database to explore further the microstructures at the same high temperature, notably to know the conditions on the Co, Ni, Cr, Ta and C contents to keep the {matrix + TaC} structure and to avoid any possible partial melting.
Assessment of the Coliform Bacterial Load of Some Drinking Water Sources in D...Scientific Review SR
Drinking water samples from 5 sachet water companies, 3 boreholes and 2 taps, collected from different locations of Dutse Metropolis of Jigawa State, Nigeria were analysed for coliform bacterial counts using the Membrane Filtration Technique. All the samples contained some amounts of total coliforms, but mostly within permissible levels. Thirty three percent (33%) of the samples from borehole, 60% from sachet water and 100% from the taps contained faecal coliforms, which indicates contamination. Cultures of the faecal coliforms obtained were morphologically identified using the gram-staining procedure and some series of biochemical tests were carried out in order to identify the organisms. The identified organisms were Escherichia coli (E. coli), Klebsiella sp. and Citrobacter sp. Presence of coliforms above the regulatory set standards indicates contamination and un-safeness of the water for drinking. Presence of organisms such as E. coli, Klebsiella sp. and Citrobacter sp. necessitates improvement in monitoring and water hygiene practices to improve the quality of drinking water in the study area.
Bio Inspired Self-Curing Composite: A Leap into Augmented EnactmentScientific Review SR
Relentless progress has been made on composite materials, their manufacturing processes and their structural design in past few decades. Nevertheless, the approval of composite materials in all engineering disciplines is constrained due to its susceptibility to various kinds of defects during manufacturing stage viz porosity, foreign body inclusion, incorrect fiber volume, bonding defect, fiber misalignment, ply misalignment, incorrect curing cycle, wavy fiber, ply cracking, delamination, fiber microstructural defects etc. Hence there was a requirement of techniques to somehow overcome these defects during the service life of composites being used in various structures and equipment. This promising field of research has made great progress over the past several years, but many procedural encounters are still to be overcome, and there exists a great need for focused research to address several areas of concern. On the other hand, nature has materials that have curing potential and repair strategies ensuring their survival. Sustained development in the field will produce new curing chemistries that possess greater stability, faster kinetics. Tailor-made placement of curing agents is dynamic research subject at the cutting edge of self-curing. New bio-imitative curing agents are closely connected to vascular networks. The purpose of this technical paper is to sort the methodology in line with ongoing research efforts in composites. A perspective on current and future self-curing approaches using this biomimetic technique is offered.
Influence of Information and Communication Technology (ICT) in Tourism Sector...Scientific Review SR
Nepal is a country blessed with natural beauty, diverse culture, majestic Himalayas, religious destination which attracts thousands of tourists every year making the tourism industry progressive to flourish. Information Communication Technology (ICT) proves to be an effective tool for strengthening the tourism industry. Thus, the purpose of this research study is to analyze about the past scenario of tourism industry, advent of ICT in tourism industry, positive impacts of ICT in tourism industry through in-depth interview with tourism experts and people who have worked for tourism since decades. This study is a form of qualitative research where narrative inquiry has been selected and the scenario has been analyzed through themes developed from the narratives. The result reveals that the emerging technology brings positive impacts to tourism industry assisting branding, promotion of the country, enhancing networks through communication and easily booking tours. The proper utilization of ICT helps to welcome tourists and to give identity of our country Nepal to the world.
Reinforcement of Bakelite Moulding Powder in Acrylonitrile Butadiene Rubber (...Scientific Review SR
The influences of two phenolic resins, that is, cashew nut oil modified phenol-formaldehyde resin (CN-m-PF) and Bakelite moulding powder (BMP), on properties of carbon black filled acrylonitrile butadiene rubber (NBR) were investigated and compared. Processability, cure characteristics, mechanical properties, thermal ageing resistance, and oil resistance of the NBR filled with various contents of phenolic resins (0-60 phr) were determined. The addition of both resins leads to a prolonged cure time with a greater value of torque difference. Regardless of the resin type, the improvement of compound processability and the enhancement of modulus and hardness of the NBR vulcanisates are observed with increasing resin content. However, many mechanical properties such as tensile strength, elongation at break and abrasion resistance are deteriorated. Thermal ageing resistance of the NBR vulcanisate is slightly improved in the presence of both resins, probably due to the dilution of NBR with the high heat-resistant phenol-formaldehyde resins. Results also disclose that all NBR vulcanisates demonstrate excellent oil resistance, regardless of the resin type and content. At any given resin content, CN-m-PF gives a better processability, higher stiffness and greater mechanical properties than BMP. However, due to its lower cost, BMP can be used to enhance stiffness of NBR vulcanisates without the risk of processing problem.
Toxic Effect of Glyphosate-Pesticide on Lipid Peroxidation Superoxide Dismuta...Scientific Review SR
The oxidative stress indices lipid peroxidation (LPO), superoxide dismutase (SOD) and catalase (CAT) in juvenile Clarias gariepinus (average weight 200.15 g) exposed to sub - lethal dose 2.40mg/L and 4.98mg/L of glyphosate was investigated over a period of days 1,5,10 and 15 in three replicates. The colorimetric analysis showed increase in lipid peroxidation from 4.55 ±2.14a1 to 12.12± 10.00a1at 2.40mg/L but remain the same at 4.98mg/L (4.55±2.14a1) compared with control (3.03±0.01a1 to 1.51±2.14b1) from day 1 to 15. The SOD activity decreased significantly with time and concentration compared with control. The Catalase activity at day 15 decreased to 0.17±0.05a1 in 2.40mg/L but further increased to 0.28±0.05b1 in 4.98mg/L compared to 0.28±0.02a1 catalase activity as control. The result suggests that glyphosate induce oxidative stress that may overwhelm the antioxidant system in juvenile catfish especially at higher concentrations with long exposure.
Wheeled robots are often utilized for various remote sensing and telerobotic applications because of their ability to navigate through dynamic environments, mostly under the partial control of a human operator. To make these robots capable to traverse through terrains of rough and uneven topography, their driving mechanisms and controllers must be very efficient at producing and controlling large mechanical power with great precision in real-time, however small the robot may be. This paper discusses an approach for designing a quad-wheeled robot, which is wirelessly controlled with a personal computer (PC) by medium-range radio frequency (RF) transceiver, to navigate through unpaved paths with little or no difficulty. An efficient servo-controlled Ackerman steering mechanism and a high-torque driving power-train were developed. The robot’s controller is programmed to receive and respond to RF control signals from the PC to perform the desired motions. The dynamics of the robot’s drivetrain is modeled and analyzed on MATLAB to predict its performances. The robot was tested on various topographies to determine its physical capabilities. Results show that the robot is capable of non-holonomically constrained motions on rough and uneven terrains.
Geometrical Analysis and Design of Tension-Actuated Ackermann Steering System...Scientific Review SR
The tension-actuated steering system is a vehicular steering design that comprises a motorized gear system, pulleys, inelastic string, main steering bar, and a strain gauge. This development is aimed to produce a steering design that could enhance the efficiency of steering systems in quad-wheeled (i.e. four-wheeled) robots. In this work, the steering system of conventional passenger vehicles and existing quad-wheeled robots are reviewed and their technical deficiencies are improved based on cost, power and production factors. Thus, the tension-actuated steering system is proposed as a solution for mechanizing steering functions in quad-wheeled robots. It is expected that this work will stimulate interest and enthusiasm.
A Study of Propensity Score on Influencing Factors of Length of Stay in Hospi...Scientific Review SR
Background: Burns are a global public health problem, which are universal and can happen to anyone. Because the physical functions in children and adults are different, the confounding factors are easy to affect the results of study. Objective: In this study, we aimed to explore influencing factors of the length of hospital stay (LOS) when the confounding factors were excluded by Propensity Score (PS) in children and adults. Methods: Patients hospitalized for burn from 2014 to 2016 were retrieved from the medical record system of a general biggest hospital in Zunyi. A database was established to analyze the influencing factors of LOS between children and adults by the PS. Results A total of 465 children (61.7% males) and 327 (69.7% males) adults were recruited. The average age was 3.61±3.57 years and 42.48±14.76 years in children and adults with burns respectively. Before PS matching, low age and skin grafting were the protective factors for LOS (Hazard Ratio [HR]=0.993 and 0.339). The risk factors of LOS were male (HR=1.234), the burn depth and total body surface area (TBSA), and burn etiology (HR=1.497). After PS matching, only skin grafting (HR=0.080) and treatment within 24 hours (HR=1.865) were the common influencing factors of LOS. Conclusion the confounding factors were excluded by the PS method, and skin grafting was still a protective factor of LOS for both children and adults. The results provide a reference for the promotion of skin grafting to reduce LOS in burn patients.
Concrete is one of the reliable, durable, economical and acceptable construction materials among the building and construction stakeholders worldwide. Performance of concrete could be threatened especially reinforced concrete by some processes such as corrosion, sulfate attack among others. Corrosion of reinforcement in reinforced concrete can be induced by carbonation process. Even though carbonation initiates corrosion, it has been gathered that carbonation could still be of immense benefits to building and construction industries if its mechanism of operation is understudied. This research work has therefore investigated the effect of carbonation on some selected mechanical properties of concrete such as compressive strength, flexural strength, water absorption and weight changes. Concrete cubes and beams of M15 grade with 0.5 % water-cement ratio were prepared and subjected to accelerated carbonation. Their compressive strength, flexural strength, water absorption and weight changes were determined in accordance with the relevant standards. The outcomes show that carbonation improves all the mechanical properties investigated. The use of carbonation can be positively explored in reinforced concrete provided there is adequate nominal cover.
Biogas Synthesis as Means of Solid Waste Management in Kampala, UgandaScientific Review SR
Cattle dung, cooked food waste, and chicken droppings mixed with coffee husks have been used separately and also as mixtures to form anaerobic digestion slurries in a bid to treat to degrade the organic fractions of these wastes and recycle the bio-fertilizer after recovering biogas. Single and mixed substrate slurries evolved significant quantities of methane within 27days together with reduced mass of soil conditioner. The volume of biogas formed in cogeneration mixtures were higher than for single substrate digestion due to the C/N ratio shifting to near 30:1 as a result of mixing. So degradation of organic pollutants was higher in mixed substrate digestion mixtures. Our study yielded average volumes ranging from 315 to 435+ 5.65.mL/L which was in agreement with what is in literature. Digestion of cattle dung, cooked waste foods, and droppings of chicken and mixed substrate slurries using sludge inoculums was very effective in degrading solid waste from homes, thus detoxifying it to bio-fertilizers. Although both single and mixed substrate digestion of waste yielded high enough volumes of biogas; digestion of slurry of mixed organic solid waste substrates is better method of waste management. Digestion of garbage from Kampala should be tested at macro levels at both ambient and mesophilic temperatures. There is need to try out the garbage digestion experiments in the semi-arid towns as well as very cold towns in Uganda.
The Influence of Partial Replacement of Some Selected Pozzolans on the Drying...Scientific Review SR
Concrete is prone to cracking and one of the major causes of cracking is drying shrinkage of the hardened concrete. This research work was carried out to study the influence of partial replacement of some selected pozzolans on the drying shrinkage of concrete. Four pozzolans used in this study, were made to replace cement at various percentages resulting in various concrete mixes. Setting time test was conducted for the various cement mixes using Vicat’s apparatus and drying shrinkage test was done for the concrete test specimens. The results of the setting time indicate that partial replacement of pozzolans with ordinary Portland cement increases both the initial and final setting time of cement as the percentage replacement increases. Similarly, drying shrinkage results show that concrete made with Groundnut Shell Ash (GSA) and Locust Bean Pod Ash (LBA) at 12% replacement will have a stable and better shrinkage resistance than the control at both 56 days and 90 days. Meanwhile, the control concrete gives a better drying shrinkage at 28 days curing. In conclusion, the results show that pozzolanas [Bamboo Leaves Ash (BLA), Locust Bean Pod Ash (LBA), Sugarcane Bagasse Ash (SBA) and Groundnut Shell Ash (GSA)] can successfully replace cement up to 12% without necessarily affecting the shrinkage ability of the produced concrete. It also shows that Groundnut Shell Ash (GSA), Locust Bean Pod Ash (LBA) and Bamboo Leaves Ash (BLA) are more resistance to drying shrinkage than the control.
Study on the Granulation of FLY Ash from Thermal Power StationScientific Review SR
The effect of the type and amount of binding substance on the yield and strength of granules prepared from fly ash was studied. The highest yield of granules was achieved with clayish slip used as binder. The granules obtained are brittle, with compression strength 0,1МРа. The apparent density of the sintered granulates was in the range1200-1500kg/m3 and the total porosity was 55-40%.
Machining Versus Molding Tolerances in Manufacturing Automotive Sealing SystemsScientific Review SR
The automotive industry has been at the forefront of converting traditional metal parts to plastics. The latter surely offer greater design freedom, opportunity for consolidation, fewer assembly operations, reduced secondary finishing, weight reduction, lower total system costs, a range of properties tailored to specific applications, the ability to withstand temperatures, immunity to most chemicals and corrosive environments. They offer processing in many colors, electrical non-conductivity (insulation from electrical shocks), good thermal breaks (“warmth-to-the-touch”), and low sound transmission (tendency to muffle noise). Nonetheless, plastics have only tapped an estimated 15% of their tremendous potential to replace metals. This is particularly to increase with newer high-performance plastics, increasing sophistication in alloying and blending technologies, and use of computer-aided design and engineering (CAD/CAE) systems. The latter enable engineers to visualize complex parts and molding tools more effectively and faster than ever before. This article identifies fundamental steps and requirements to conduct an efficient and successful conversion of metallic parts to plastics, reviewing the replacement design process from concept to production; an under-the-hood rear retainer for Ford Motor Company is detailed as a case study.
Sinthesis and Properties of Marble-Like Glass-Ceramics Using of Ash from Ther...Scientific Review SR
Color marble-like glass-ceramic materials were obtained through thermal treatment of glasses of the system CaO-Al2O3-SiO2 by using natural materials with the introduction of waste materials - ash from thermal power plants (TPP). The melting of the glass batch was in corundum crucibles at 1450oC with an isothermal hold of 60 min. The glasses obtained was fritted in distilled water and dried for 6 hours at 100oC, then completely crushed and divided into fractions with grain size of 0.8 mm, 1.0 mm, 2 mm, 2.5 mm and over 2.5 mm. It was found that the use of ash from TPP lead to higher values of degree of transformation (crystallization) than using base composition. Values of Avramy parameter’s in the range n=1,0 ÷ 1,6 are showed that crystallization of the glass frit is largely heterogeneous and crystal growing starts from the surface. The introduction of ash from TPP to native glasses carry out to significant reduction of energy of crystallization by Ес=289 kJ/mol to Ec=221 kJ/mol. The glass-ceramic materials were obtained through a one stage crystallization - 1050÷1070оС and an isothermal hold of 60 min., colored white, yellow brown to dark brown. The main crystalline phase in glass-ceramics is β-vollastonite with needle habit, size of crystals - ĺ = 40 ÷ 120 μm and d <5 μm in quantities 37 ÷ 42%. As secondary phases depending on the amount of ash have been identified - the anorthite, gehlenite and α-quartz with prismatic habit were appeared. The obtained glass-ceramic materials have a marble-like effect and technical parameters compared with natural granite and marble and have higher values of density, micro hardness, speed grinding, bending strength and chemical resistance. That’s why they can be used in construction such as lining materials.
Natural farming @ Dr. Siddhartha S. Jena.pptxsidjena70
A brief about organic farming/ Natural farming/ Zero budget natural farming/ Subash Palekar Natural farming which keeps us and environment safe and healthy. Next gen Agricultural practices of chemical free farming.
Diabetes is a rapidly and serious health problem in Pakistan. This chronic condition is associated with serious long-term complications, including higher risk of heart disease and stroke. Aggressive treatment of hypertension and hyperlipideamia can result in a substantial reduction in cardiovascular events in patients with diabetes 1. Consequently pharmacist-led diabetes cardiovascular risk (DCVR) clinics have been established in both primary and secondary care sites in NHS Lothian during the past five years. An audit of the pharmaceutical care delivery at the clinics was conducted in order to evaluate practice and to standardize the pharmacists’ documentation of outcomes. Pharmaceutical care issues (PCI) and patient details were collected both prospectively and retrospectively from three DCVR clinics. The PCI`s were categorized according to a triangularised system consisting of multiple categories. These were ‘checks’, ‘changes’ (‘change in drug therapy process’ and ‘change in drug therapy’), ‘drug therapy problems’ and ‘quality assurance descriptors’ (‘timer perspective’ and ‘degree of change’). A verified medication assessment tool (MAT) for patients with chronic cardiovascular disease was applied to the patients from one of the clinics. The tool was used to quantify PCI`s and pharmacist actions that were centered on implementing or enforcing clinical guideline standards. A database was developed to be used as an assessment tool and to standardize the documentation of achievement of outcomes. Feedback on the audit of the pharmaceutical care delivery and the database was received from the DCVR clinic pharmacist at a focus group meeting.
Artificial Reefs by Kuddle Life Foundation - May 2024punit537210
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Willie Nelson is a name that resonates within the world of music and entertainment. Known for his unique voice, and masterful guitar skills. and an extraordinary career spanning several decades. Nelson has become a legend in the country music scene. But, his influence extends far beyond the realm of music. with ventures in acting, writing, activism, and business. This comprehensive article delves into Willie Nelson net worth. exploring the various facets of his career that have contributed to his large fortune.
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Introduction
Willie Nelson net worth is a testament to his enduring influence and success in many fields. Born on April 29, 1933, in Abbott, Texas. Nelson's journey from a humble beginning to becoming one of the most iconic figures in American music is nothing short of inspirational. His net worth, which estimated to be around $25 million as of 2024. reflects a career that is as diverse as it is prolific.
Early Life and Musical Beginnings
Humble Origins
Willie Hugh Nelson was born during the Great Depression. a time of significant economic hardship in the United States. Raised by his grandparents. Nelson found solace and inspiration in music from an early age. His grandmother taught him to play the guitar. setting the stage for what would become an illustrious career.
First Steps in Music
Nelson's initial foray into the music industry was fraught with challenges. He moved to Nashville, Tennessee, to pursue his dreams, but success did not come . Working as a songwriter, Nelson penned hits for other artists. which helped him gain a foothold in the competitive music scene. His songwriting skills contributed to his early earnings. laying the foundation for his net worth.
Rise to Stardom
Breakthrough Albums
The 1970s marked a turning point in Willie Nelson's career. His albums "Shotgun Willie" (1973), "Red Headed Stranger" (1975). and "Stardust" (1978) received critical acclaim and commercial success. These albums not only solidified his position in the country music genre. but also introduced his music to a broader audience. The success of these albums played a crucial role in boosting Willie Nelson net worth.
Iconic Songs
Willie Nelson net worth is also attributed to his extensive catalog of hit songs. Tracks like "Blue Eyes Crying in the Rain," "On the Road Again," and "Always on My Mind" have become timeless classics. These songs have not only earned Nelson large royalties but have also ensured his continued relevance in the music industry.
Acting and Film Career
Hollywood Ventures
In addition to his music career, Willie Nelson has also made a mark in Hollywood. His distinctive personality and on-screen presence have landed him roles in several films and television shows. Notable appearances include roles in "The Electric Horseman" (1979), "Honeysuckle Rose" (1980), and "Barbarosa" (1982). These acting gigs have added a significant amount to Willie Nelson net worth.
Television Appearances
Nelson's char
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The carbon cycle is a critical component of Earth's environmental system, governing the movement and transformation of carbon through various reservoirs, including the atmosphere, oceans, soil, and living organisms. This complex cycle involves several key processes such as photosynthesis, respiration, decomposition, and carbon sequestration, each contributing to the regulation of carbon levels on the planet.
Human activities, particularly fossil fuel combustion and deforestation, have significantly altered the natural carbon cycle, leading to increased atmospheric carbon dioxide concentrations and driving climate change. Understanding the intricacies of the carbon cycle is essential for assessing the impacts of these changes and developing effective mitigation strategies.
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In-depth exploration of the carbon cycle reveals the delicate balance required to sustain life and the urgent need to address anthropogenic influences. Through research, education, and policy, we can work towards restoring equilibrium in the carbon cycle and ensuring a sustainable future for generations to come.
"Understanding the Carbon Cycle: Processes, Human Impacts, and Strategies for...
Prediction of Extreme Wind Speed Using Artificial Neural Network Approach
1. Scientific Review
ISSN(e): 2412-2599, ISSN(p): 2413-8835
Vol. 2, No. 1, pp: 8-13, 2016
URL: http://arpgweb.com/?ic=journal&journal=10&info=aims
8
Academic Research Publishing Group
Prediction of Extreme Wind Speed Using Artificial Neural
Network Approach
N. Vivekanandan Central Water and Power Research Station, Pune, Maharashtra, India
1. Introduction
Wind is renewable source of energy and is almost the fastest growing energy resource in the world, which offers
many benefits to human beings. Wind energy has been getting immense attention because renewable energies have
got tremendous focus. Due to increase in cost of fossil fuel and the various environmental problems, it is important
to appreciate the potential of electricity generation from nonconventional sources. The effective use of wind energy
is the conversion of wind power into valuable forms of electricity. The distribution of wind speed is important for
power generators [1]. For the purpose, the predicted variations of meteorological parameters such as wind speed,
relative humidity, solar radiation, air temperature, etc. are needed in the renewable industry for design, performance
analysis, and running cost estimation of the systems. Moreover, for proper and efficient utilization of wind power, it
is important to know the statistical characteristics, persistence, availability, diurnal variation and prediction of wind
speed. The wind characteristics are needed for site selection, performance prediction and planning of wind turbines.
Of these characteristics, the prediction of mean monthly and daily wind speed is very important. For the purpose,
number of methods has been employed for the wind power forecasting. The wind power forecasting methods can be
generally categorized into six groups such as persistence, physical, statistical, spatial correlation, artificial
intelligence network and hybrid [2]. In this paper, application of ANN method in prediction of wind speed is
discussed with illustrative example.
2. Theoretical Description of ANN
ANN modelling procedures adapt to complexity of input-output patterns and accuracy goes on increasing as
more and more data become available. Figure 1 presents the architecture of ANN that consists of input layer, hidden
layer, and output layer [3]. In turn, these layers have a certain number of neurons or units, so the units are called as
input units, hidden units and output units. From ANN structure, it can be easily understood that input units receive
data from external sources to the network and send them to the hidden units, in turn, the hidden units send and
receive data only from other units in the network, and output units receive and produce data generated by the
network, which goes out of the system. In this process, a typical problem is to estimate the output as a function of
the input. This unknown function may be approximated by a superposition of certain activation functions such as
tangent, sigmoid and polynomial. A common threshold function used in ANN is the sigmoid function (f(S))
expressed by Eq. (1), which provides an output in the range of 0≤f(S)<1.
Abstract: Prediction of an accurate wind speed of wind farms is necessary because of the intermittent nature
of wind for any region. Number of methods such as persistence, physical, statistical, spatial correlation, artificial
intelligence network and hybrid are generally available for prediction of wind speed. In this paper, ANN based
methods viz., Multi Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are used. The
performance of the networks applied for prediction of wind speed is evaluated by model performance indicators
viz., Correlation Coefficient (CC), Model Efficiency (MEF) and Mean Absolute Percentage Error (MAPE).
Meteorological parameters such as maximum and minimum temperature, air pressure, solar radiation and
altitude are considered as input units for MLP and RBF networks to predict the extreme wind speed at Delhi.
The study shows the values of CC, MEF and MAPE between the observed and predicted wind speed (using
MLP) are computed as 0.992, 95.4% and 4.3% respectively while training the network data. For RBF network,
the values of CC, MEF and MAPE are computed as 0.992, 95.9% and 3.0% respectively. The model
performance analysis indicates the RBF is better suited network among two different networks studied for
prediction of extreme wind speed at Delhi.
Keywords: Artificial neural network; Multi layer perception; Correlation coefficient; Mean absolute percentage error;
Model efficiency; Radial basis function; Wind speed.
2. Scientific Review, 2016, 2(1): 8-13
9
1
ii Sexp1)S(f
and )S(f)S(F i
'
i … (1)
i
N
1i
ijii OWIS
, j=1,2,3,…..M … (2)
where Si is the characteristic function of ith
layer, Ii is the input unit of ith
layer, Oi is the output unit of ith
layer, Wij is
the synaptic weights between ith
input and jth
hidden layers, N is the number of observations and M is the number of
neurons in the hidden layer [4]. The sigmoid function is chosen for mathematical convenience because it resembles a
hard-limiting step function for extremely large positive and negative values of the incoming signal and also gives
sufficient information about the response of the processing unit to inputs that are close to the threshold value.
Figure-1. Architecture of ANN
3. Literature Review of ANN
With the development of Artificial Intelligence (AI), a number of various AI methods have been developed for
prediction of wind speed. The new developed methods include Artificial Neural Network (ANN), Adaptive Neuro-
Fuzzy Inference System, Fuzzy Logic, Support Vector Machine, Neuro-Fuzzy Network (NFN) and Evolutionary
Optimization Algorithm. Out of these methods, ANN could deal with non-linear and complex problems in terms of
classification or forecasting. The ANN models can represent a complex nonlinear relationship and extract the
dependence between variables through the training process [5]. In ANN, number of training algorithms such as Multi
Layer Perceptron (MLP), Recurrent (REC), Radial Basis Function (RBF), Ridgelet and Adaptive Linear Element
(ALE) are used for training the network. Sfetsos [6] applied ANN method for forecasting of mean hourly wind speed
data using time series analysis. The proposed methodology has an additional benefit for utility that have significant
wind penetration level and use hourly interval for power system operational procedures such as economic dispatch
and unit commitment. Chang [7] described wind power forecasting methodologies using MLP network. The
developed model for short-term wind forecasting showed a very good accuracy to be used by a 2400kw wind energy
conversion system in Taichung coast for the energy supply. More and Deo [8] presented two wind forecasting
methodologies based on MLP and REC networks. They also found that the results obtained from ANN methods are
more accurate than traditional statistical time series analysis.
Chang [9] adopted a method to do time series prediction of wind power generation using RBF network. They
expressed that the good agreement between the realistic values and forecasting values are obtained; and the
numerical results showed that the proposed forecasting method is accurate and reliable. Li and Shi [10] compared
three types of networks namely, ALE, MLP and RBF to forecast the wind speed. They found that no single ANN
model outperforms others universally in terms of all evaluation metrics even for the same wind data set. Moreover,
the selection of the type of ANN for best performance is also dependent upon the data sources. However, the
research reports indicated that there is a general agreement in applying ANN based method for prediction of wind
speed. Therefore, in the present study, ANN based methods viz., MLP and RBF networks are used to predict the
wind speed with illustrative example.
3.1. Multi-Layer Perceptron Network
MLP network is the most widely used for prediction of wind speed and its architecture with single hidden layer
is shown in Figure 1. Gradient descent is the most commonly used supervised training algorithm in MLP in which
3. Scientific Review, 2016, 2(1): 8-13
10
each input unit of the training data set is passed through the network from the input layer to output layer [11]. The
network output is compared with the desired target output and output error ( E ) is computed using Eq. (3).
N
1i
2*
ii XX
2
1
E … (3)
where, iX is the observed wind speed for ith
sample and *
iX is the predicted wind speed for ith
sample.
1MW
W
E
)M(W ij
ij
ij
… (4)
where, ijW is the synaptic weights between input and hidden layers, )M(Wij is the weight increments between ith
and jth
units during M neurons (units) and )1M(Wij is the weight increments between ith
and jth
units during 1M
neurons. In MLP network, momentum factor ( α ) is used to speed up training in very flat regions of the error surface
to prevent oscillations in the weights and learning rate ( ε ) is used to increase the chance of avoiding the training
process being trapped in local minima instead of global minima [12].
3.2. Radial Basis Function Network
RBF network is supervised and three-layered feed forward neural network. The hidden layer of RBF network
consists of a number of nodes and a parameter vector, which can be considered the weight vector. In RBF, the
standard Euclidean distance is used to measure the distance of an input vector from the center. The design of neural
networks is a curve-fitting problem in a high dimensional space in RBF. Training the RBF implies finding the set of
basis nodes and weights. Therefore, the learning process is to find the best fit to the training data [13]. The transfer
functions of the nodes are governed by nonlinear functions that is assumed to be an approximation of the influence
that data points have at the center. The transfer function of a RBF is mostly built up of Gaussian rather than sigmoid.
The Gaussian functions decrease with distance from the center. The transfer functions of the nodes are governed by
nonlinear functions that is assumed to be an approximation of the influence that data points have at the center.
The Euclidean length is represented by jr that measures the radial distance between the datum
vector )X,...X,X(X M21
and the radial center )W,...W,W(X Mjj2j1
)j(
can be written as:
2/1
M
1i
2
iji
)j(
j WXXXr
… (5)
where jr is the Euclidean norm, () is the activation function and ijW is the connecting weight between the
ith
hidden unit and jth
output unit. A suitable transfer function is then applied to rj to give )k(
j XXΦ)r(Φ .
Finally, the output layer (k-1) receives a weighted linear combination of )r( j .
N
1j
N
1j
)j()k(
j0j
)k(
j0
)k(
XXΦcW)r(ΦcWX … (6)
where, )r( j is the response of the jth
hidden unit and 0W is the bias term. For both MLP and RBF networks, the
units (or) neurons in the hidden layer are decided by the following equation:
N
PP
M S
2
OI
H
… (7)
where, MH is the number of neurons in hidden layer, NS is the number of data samples used in MLP and RBF
networks, PI is the number of input parameter and PO is the number of output parameter [14].
3.3. Normalization of Data
By considering the nature of sigmoid function adopted in ANN, the training data set values are normalized
between 0 and 1 using Eq. (8) and passed into the network [15]. After the completion of training, the output values
are denormalized to provide the results in original domain.
ii
ii
i
XMinXMax
XMinX
XNOR
… (8)
where, iXNOR is the normalized value of iX , iXMin is the series minimum value of iX and iXMax is the series
maximum value of iX .
3.4. Model Performance Analysis
The performance of predicted wind speed using MLP and RBF networks are evaluated by Model Performance
Indicators (MPIs) viz., Correlation Coefficient (CC), Model Efficiency (MEF) and Mean Absolute Percentage Error
(MAPE), and are:
4. Scientific Review, 2016, 2(1): 8-13
11
CC =
N
1i
2
**
i
N
1i
2
i
N
1i
**
ii
XXXX
XXXX … (9)
MEF (%) =
100*
XX
XX
1 N
1i
i
N
1i
2*
ii
2
… (10)
MAPE(%) = 100*
X
XX
N
1 N
1i i
*
ii
… (11)
where X is the average observed wind speed and *
X is the average predicted wind speed [16].
4. Application
In this paper, a study on prediction of annual extreme wind speed (km/hr) for Delhi region was carried out. ANN
based methods viz., MLP and RBF networks were used for training the network. For MLP and RBF networks, the
meteorological parameters viz., minimum and maximum temperature, solar radiation, air pressure and altitude were
considered as the input units and predicted annual extreme wind speed was the desired output unit. Figure 2 gives the
ANN architecture for prediction of annual extreme wind speed. The annual series of meteorological parameters was
derived from the daily data recorded at Delhi for the period 1969 to 2013 and used. The data for the period 1969 to
1998 was used for training the network and data for the period 1999 to 2013 was used for testing the network.
Figure-2. ANN architecture for prediction of wind speed
5. Results and Discussions
Statistical software, namely, SPSS Neural Connection was used to train the network data with different
combinations of parameters to determine optimum network architectures of MLP and RBF networks for prediction
of annual extreme wind speed at Delhi.
5.1. Prediction of Wind Speed using MLP and RBF Networks
In the present study, the input units were normalized and applied to the network as the units of the parameters
are different. The momentum factor ( α ) and learning rate ( ε ) were fixed as 0.8 and 0.07 while optimizing the
network architecture of MLP. The network data was trained with the optimum network architectures of MLP and
RBF, as given in Table 1. The networks were tested with model parameters for prediction of wind speed. The output
unit was denormalized to obtain the value of annual maximum extreme wind speed in km/hr. The model
performance of MLP and RBF networks were evaluated by MPIs and also given in Table 1 for the region under
study.
5. Scientific Review, 2016, 2(1): 8-13
12
Table-1. Network architectures with MPIs of MLP and RBF networks
Network Architecture
and MPIs
MLP RBF
Training Testing Training Testing
Network Architecture 5-10-1 5-15-1
CC 0.992 0.990 0.992 0.990
MEF (%) 95.4 94.9 95.9 94.7
MAPE (%) 4.3 4.5 3.0 3.8
From Table 1, it may be noted that: (i) The results of MPIs obtained from RBF network is comparatively better
than the corresponding values of MLP network while training the network data and therefore the network
architecture of RBF is better suited network for prediction of wind speed for Delhi; (ii) The percentage of MEF is
computed as about 95% while testing the data set with RBF network; (iii) The percentages of MAPE obtained from
MLP and RBF networks are 4.5% and 3.8% respectively while testing the network data; and (iv) There is generally a
good correlation between the observed and predicted wind speed using MLP and RBF networks, with CC values
vary between 0.990 and 0.992.
Based on the results obtained from performance analysis with the aid of MPIs, it was observed that the RBF
network gave high prediction accuracy than MLP network for Delhi. Figure 3 give the plots of observed and
predicted wind speed (using MLP and RBF networks) for Delhi.
Figure-3. Plots of observed and predicted wind speed (using MLP and RBF networks)
5.2. Analysis Based on Descriptive Statistics
The descriptive statistics such as average, Standard Deviation (SD), Coefficient of Variation (CV), Coefficient
of Skewness (CS) and Coefficient of Kurtosis (CK) for the observed and predicted wind speed (using MLP and RBF
networks) were computed and given in Table 2.
Table-2. Descriptive statistics of observed and predicted wind speed for Delhi
Statistical parameters Observed
wind speed
Predicted wind speed
MLP RBF
Training Testing Training Testing Training Testing
Average (km/hr) 67.8 64.1 67.0 62.0 65.8 63.1
SD (km/hr) 15.5 15.6 12.8 12.6 14.0 13.6
CV (%) 22.9 24.3 19.1 20.3 21.3 21.6
CS -0.013 -0.006 0.068 0.120 0.103 0.226
CK -1.815 -1.319 -1.716 -1.022 -1.747 -1.095
From Table 2, it may be noted that the percentage of variation on the average predicted wind speed using MLP
network, with reference to average observed wind speed, is 1.2% during training period and 3.3% during testing
period. For RBF network, percentage of variation on the average predicted wind speed with reference to average
observed wind speed during training and testing periods were computed as 2.9% and 1.6% respectively.
6. Scientific Review, 2016, 2(1): 8-13
13
6. Conclusions
The paper described the procedures involved in prediction of wind speed using MLP and RBF networks for
Delhi. From the results of data analysis, the following conclusions were drawn from the study:
i) Optimum network architectures such as 5-10-1 of MLP and 5-15-1 of RBF were used for training the
network data.
ii) The values of CC, MEF and MAPE between the observed and predicted wind speed (using MLP network)
were computed as 0.992, 95.4% and 4.3% respectively while training the network data. For RBF network,
the values of CC, MEF and MAPE were found to be 0.992, 95.9% and 3.0% respectively.
iii) The values of CC, MEF and MAPE between the observed and predicted wind speed (using MLP network)
were found to be 0.990, 94.9% and 4.5% respectively while testing the network data. For RBF network, the
values of CC, MEF and MAPE were computed as 0.990, 94.7% and 3.8% respectively.
iv) Analysis based on MPIs and descriptive statistics showed that the RBF network is comparatively better than
MLP network for the data under study. MLP and RBF networks were tested by predicting wind speed for
Delhi for which measured data are available; and the results indicated the developed RBF network gives
high prediction accuracy.
v) The percentage of variation on the average predicted wind speed with reference to average observed wind
speed was found to be 1.6% while testing the network data with RBF network, which is comparatively less
than the corresponding value of MLP network.
vi) The results presented in the paper would be helpful to the stakeholders for planning, design and
management of hydraulic and civil structures in Delhi region.
Acknowledgements
The author is grateful to Dr. M. K. Sinha, Director, Central Water and Power Research Station, Pune, for providing
the research facilities to carry out the study. The author is also thankful to M/s Nuclear Power Corporation of India
Limited, Mumbai for supply of temperature data used in the study.
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