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.
Software testing effort estimation with cobb douglas function a practical app...eSAT Publishing House
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.
A hybrid fuzzy ann approach for software effort estimationijfcstjournal
Software development effort estimation is one of the major activities in software project management.
During the project proposal stage there is high probability of estimates being made inaccurate but later on
this inaccuracy decreases. In the field of software development there are certain matrices, based on which
the effort estimation is being made. Till date various methods has been proposed for software effort
estimation, of which the non algorithmic methods, like artificial intelligence techniques have been very
successful. A Hybrid Fuzzy-ANN model, known as Adaptive Neuro Fuzzy Inference System (ANFIS) is more
suitable in such situations. The present paper is concerned with developing software effort estimation
model based on ANFIS. The present study evaluates the efficiency of the proposed ANFIS model, for which
COCOMO81 datasets has been used. The result so obtained has been compared with Artificial Neural
Network (ANN) and Intermediate COCOCMO model developed by Boehm. The results were analyzed using
Magnitude of Relative Error (MRE) and Root Mean Square Error (RMSE). It is observed that the ANFIS
provided better results than ANN and COCOMO model.
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...paperpublications3
Abstract: Engineering design problems are complex by nature because of their critical objective functions involving many variables and Constraints. Engineers have to ensure the compatibility with the imposed specifications keeping the manufacturing costs low. Moreover, the methodology may vary according to the design problem.
The main issue is to choose the proper tool for optimization. In the earlier days, a design problem was optimized by some of the conventional optimization techniques like gradient Search, evolutionary optimization, random search etc. These are known as classical methods.
The method is to be properly Chosen depending on the nature of the problem- an incorrect choice may sometimes fail to give the optimal solution. So the methods are less robust.
Now-a-days soft-computing techniques are being widely used for optimizing a function. These are more robust. Genetic algorithm is one such method. It is an effective tool in the realm of stochastic optimization (non-classical). The algorithm produces many strings and generation to reach the optimal point.
The main objective of the paper is to optimize engineering design problems using Genetic Algorithm and to analyze how the algorithm reaches the optima effectively and closely. We choose a mathematical expression for the objective function in terms of the design variables and optimize the same under given constraints using GA.
Software testing effort estimation with cobb douglas function a practical app...eSAT Publishing House
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.
A hybrid fuzzy ann approach for software effort estimationijfcstjournal
Software development effort estimation is one of the major activities in software project management.
During the project proposal stage there is high probability of estimates being made inaccurate but later on
this inaccuracy decreases. In the field of software development there are certain matrices, based on which
the effort estimation is being made. Till date various methods has been proposed for software effort
estimation, of which the non algorithmic methods, like artificial intelligence techniques have been very
successful. A Hybrid Fuzzy-ANN model, known as Adaptive Neuro Fuzzy Inference System (ANFIS) is more
suitable in such situations. The present paper is concerned with developing software effort estimation
model based on ANFIS. The present study evaluates the efficiency of the proposed ANFIS model, for which
COCOMO81 datasets has been used. The result so obtained has been compared with Artificial Neural
Network (ANN) and Intermediate COCOCMO model developed by Boehm. The results were analyzed using
Magnitude of Relative Error (MRE) and Root Mean Square Error (RMSE). It is observed that the ANFIS
provided better results than ANN and COCOMO model.
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...paperpublications3
Abstract: Engineering design problems are complex by nature because of their critical objective functions involving many variables and Constraints. Engineers have to ensure the compatibility with the imposed specifications keeping the manufacturing costs low. Moreover, the methodology may vary according to the design problem.
The main issue is to choose the proper tool for optimization. In the earlier days, a design problem was optimized by some of the conventional optimization techniques like gradient Search, evolutionary optimization, random search etc. These are known as classical methods.
The method is to be properly Chosen depending on the nature of the problem- an incorrect choice may sometimes fail to give the optimal solution. So the methods are less robust.
Now-a-days soft-computing techniques are being widely used for optimizing a function. These are more robust. Genetic algorithm is one such method. It is an effective tool in the realm of stochastic optimization (non-classical). The algorithm produces many strings and generation to reach the optimal point.
The main objective of the paper is to optimize engineering design problems using Genetic Algorithm and to analyze how the algorithm reaches the optima effectively and closely. We choose a mathematical expression for the objective function in terms of the design variables and optimize the same under given constraints using GA.
Overview of soft intelligent computing technique for supercritical fluid extr...IJAAS Team
Optimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent factors. Recently there are growing interest in applying smart system or artificial technique to model and simulate a chemical process and also to predict, compute, classify and optimize as well as for process control. This system works by generalizing the experimental result and the process behavior and finally predict and estimate the problem. This smart system is a major assistance in the development of process from laboratory to pilot or industrial. The main advantage of intelligent systems is that the predictions can be performed easily, fast, and accurate way, which physical models unable to do. This paper shares several works that have been utilizing intelligent systems for modeling and simulating the supercritical fluid extraction process.
Review on Algorithmic and Non Algorithmic Software Cost Estimation Techniquesijtsrd
Effective software cost estimation is the most challenging and important activities in software development. Developers want a simple and accurate method of efforts estimation. Estimation of the cost before starting of work is a prediction and prediction always not accurate. Software effort estimation is a very critical task in the software engineering and to control quality and efficiency a suitable estimation technique is crucial. This paper gives a review of various available software effort estimation methods, mainly focus on the algorithmic model and non algorithmic model. These existing methods for software cost estimation are illustrated and their aspect will be discussed. No single technique is best for all situations, and thus a careful comparison of the results of several approaches is most likely to produce realistic estimation. This paper provides a detailed overview of existing software cost estimation models and techniques. This paper presents the strength and weakness of various cost estimation methods. This paper focuses on some of the relevant reasons that cause inaccurate estimation. Pa Pa Win | War War Myint | Hlaing Phyu Phyu Mon | Seint Wint Thu "Review on Algorithmic and Non-Algorithmic Software Cost Estimation Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26511.pdfPaper URL: https://www.ijtsrd.com/engineering/-/26511/review-on-algorithmic-and-non-algorithmic-software-cost-estimation-techniques/pa-pa-win
Comparison of Cost Estimation Methods using Hybrid Artificial Intelligence on...IJERA Editor
Cost estimating at schematic design stage as the basis of project evaluation, engineering design, and cost
management, plays an important role in project decision under a limited definition of scope and constraints in
available information and time, and the presence of uncertainties. The purpose of this study is to compare the
performance of cost estimation models of two different hybrid artificial intelligence approaches: regression
analysis-adaptive neuro fuzzy inference system (RANFIS) and case based reasoning-genetic algorithm (CBRGA)
techniques. The models were developed based on the same 50 low-cost apartment project datasets in
Indonesia. Tested on another five testing data, the models were proven to perform very well in term of accuracy.
A CBR-GA model was found to be the best performer but suffered from disadvantage of needing 15 cost drivers
if compared to only 4 cost drivers required by RANFIS for on-par performance.
1. Write test cases from given software models using the following test
design techniques. (K3)
a equivalence partitioning;
b boundary value analysis;
c decision tables;
d state transition testing.
2. Understand the main purpose of each of the four techniques, what level and type of testing could use the technique, and how coverage may be measured. (K2)
3. Understand the concept of use case testing and its benefits.
backlink:
http://sif.uin-suska.ac.id/
http://fst.uin-suska.ac.id/
http://www.uin-suska.ac.id/
A HYBRID ALGORITHM BASED ON INVASIVE WEED OPTIMIZATION ALGORITHM AND GREY WOL...ijaia
In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm represents invasive weed optimization. This algorithm is a random numerical algorithm and the second algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds are a serious threat to cultivated plants because of their adaptability and are a threat to the overall planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm. The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new hybridization process between the previous algorithms GWO and IWO and we will symbolize the new algorithm IWOGWO.Comparing the suggested hybrid algorithm with the original algorithms it results were excellent. The optimum solution was found in most of test functions.
A HYBRID ALGORITHM BASED ON INVASIVE WEED OPTIMIZATION ALGORITHM AND GREY WOL...gerogepatton
In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm represents invasive weed optimization. This algorithm is a random numerical algorithm and the second algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds are a serious threat to cultivated plants because of their adaptability and are a threat to the overall planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm. The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new hybridization process between the previous algorithms GWO and IWO and we will symbolize the new algorithm IWOGWO. Comparing the suggested hybrid algorithm with the original algorithms it results were excellent. The optimum solution was found in most of test functions.
Specification based or black box techniques 3alex swandi
Alex Swandi
Program Studi S1 Sistem Informasi
Fakultas Sains dan Teknologi
Universitas Islam Negeri Sultan Syarif Kasim Riau
Backlink ke website resmi kampus:
http://sif.uin-suska.ac.id/
http://fst.uin-suska.ac.id/
http://www.uin-suska.ac.id/
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
Signal classification of second order cyclostationarity signals using bt scld...eSAT Publishing House
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
Overview of soft intelligent computing technique for supercritical fluid extr...IJAAS Team
Optimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent factors. Recently there are growing interest in applying smart system or artificial technique to model and simulate a chemical process and also to predict, compute, classify and optimize as well as for process control. This system works by generalizing the experimental result and the process behavior and finally predict and estimate the problem. This smart system is a major assistance in the development of process from laboratory to pilot or industrial. The main advantage of intelligent systems is that the predictions can be performed easily, fast, and accurate way, which physical models unable to do. This paper shares several works that have been utilizing intelligent systems for modeling and simulating the supercritical fluid extraction process.
Review on Algorithmic and Non Algorithmic Software Cost Estimation Techniquesijtsrd
Effective software cost estimation is the most challenging and important activities in software development. Developers want a simple and accurate method of efforts estimation. Estimation of the cost before starting of work is a prediction and prediction always not accurate. Software effort estimation is a very critical task in the software engineering and to control quality and efficiency a suitable estimation technique is crucial. This paper gives a review of various available software effort estimation methods, mainly focus on the algorithmic model and non algorithmic model. These existing methods for software cost estimation are illustrated and their aspect will be discussed. No single technique is best for all situations, and thus a careful comparison of the results of several approaches is most likely to produce realistic estimation. This paper provides a detailed overview of existing software cost estimation models and techniques. This paper presents the strength and weakness of various cost estimation methods. This paper focuses on some of the relevant reasons that cause inaccurate estimation. Pa Pa Win | War War Myint | Hlaing Phyu Phyu Mon | Seint Wint Thu "Review on Algorithmic and Non-Algorithmic Software Cost Estimation Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26511.pdfPaper URL: https://www.ijtsrd.com/engineering/-/26511/review-on-algorithmic-and-non-algorithmic-software-cost-estimation-techniques/pa-pa-win
Comparison of Cost Estimation Methods using Hybrid Artificial Intelligence on...IJERA Editor
Cost estimating at schematic design stage as the basis of project evaluation, engineering design, and cost
management, plays an important role in project decision under a limited definition of scope and constraints in
available information and time, and the presence of uncertainties. The purpose of this study is to compare the
performance of cost estimation models of two different hybrid artificial intelligence approaches: regression
analysis-adaptive neuro fuzzy inference system (RANFIS) and case based reasoning-genetic algorithm (CBRGA)
techniques. The models were developed based on the same 50 low-cost apartment project datasets in
Indonesia. Tested on another five testing data, the models were proven to perform very well in term of accuracy.
A CBR-GA model was found to be the best performer but suffered from disadvantage of needing 15 cost drivers
if compared to only 4 cost drivers required by RANFIS for on-par performance.
1. Write test cases from given software models using the following test
design techniques. (K3)
a equivalence partitioning;
b boundary value analysis;
c decision tables;
d state transition testing.
2. Understand the main purpose of each of the four techniques, what level and type of testing could use the technique, and how coverage may be measured. (K2)
3. Understand the concept of use case testing and its benefits.
backlink:
http://sif.uin-suska.ac.id/
http://fst.uin-suska.ac.id/
http://www.uin-suska.ac.id/
A HYBRID ALGORITHM BASED ON INVASIVE WEED OPTIMIZATION ALGORITHM AND GREY WOL...ijaia
In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm represents invasive weed optimization. This algorithm is a random numerical algorithm and the second algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds are a serious threat to cultivated plants because of their adaptability and are a threat to the overall planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm. The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new hybridization process between the previous algorithms GWO and IWO and we will symbolize the new algorithm IWOGWO.Comparing the suggested hybrid algorithm with the original algorithms it results were excellent. The optimum solution was found in most of test functions.
A HYBRID ALGORITHM BASED ON INVASIVE WEED OPTIMIZATION ALGORITHM AND GREY WOL...gerogepatton
In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm represents invasive weed optimization. This algorithm is a random numerical algorithm and the second algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds are a serious threat to cultivated plants because of their adaptability and are a threat to the overall planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm. The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new hybridization process between the previous algorithms GWO and IWO and we will symbolize the new algorithm IWOGWO. Comparing the suggested hybrid algorithm with the original algorithms it results were excellent. The optimum solution was found in most of test functions.
Specification based or black box techniques 3alex swandi
Alex Swandi
Program Studi S1 Sistem Informasi
Fakultas Sains dan Teknologi
Universitas Islam Negeri Sultan Syarif Kasim Riau
Backlink ke website resmi kampus:
http://sif.uin-suska.ac.id/
http://fst.uin-suska.ac.id/
http://www.uin-suska.ac.id/
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
Signal classification of second order cyclostationarity signals using bt scld...eSAT Publishing House
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
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
Performance analysis of various parameters by comparison of conventional pitc...eSAT Publishing House
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
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
Characterization of mixed crystals of sodium chlorate and sodium bromate and ...eSAT Publishing House
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
Loc, los and loes at speed testing methodologies for automatic test pattern g...eSAT Publishing House
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
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
Semicompatibility and fixed point theorem in fuzzy metric space using implici...eSAT Publishing House
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.
Text independent speaker recognition using combined lpc and mfc coefficientseSAT Publishing House
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
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.
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.
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.
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.
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
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
This paper presents a set of methods that uses a genetic algorithm for automatic test-data generation in
software testing. For several years researchers have proposed several methods for generating test data
which had different drawbacks. In this paper, we have presented various Genetic Algorithm (GA) based test
methods which will be having different parameters to automate the structural-oriented test data generation
on the basis of internal program structure. The factors discovered are used in evaluating the fitness
function of Genetic algorithm for selecting the best possible Test method. These methods take the test
populations as an input and then evaluate the test cases for that program. This integration will help in
improving the overall performance of genetic algorithm in search space exploration and exploitation fields
with better convergence rate.
Modified artificial immune system for single row facility layout problemIAEME Publication
One of the main optimization algorithms currently available in the research field is an Artificial Immune System where abundant applications are using this algorithm for clustering and patter recognition processes. These algorithms are providing more effective optimized results in multi-model optimization problems than Genetic Algorithm.
Design and Implementation of a Multi-Agent System for the Job Shop Scheduling...CSCJournals
Job shop scheduling is one of the strongly NP-complete combinatorial optimization problems. Developing effective search methods is always an important and valuable work. Meta-heuristic methods such as genetic algorithms are widely applied to find optimal or near-optimal solutions for the job shop scheduling problem. Parallelizing genetic algorithms is one of the best approaches that can be used to enhance the performance of these algorithms. In this paper, we propose an agent-based parallel genetic algorithm for job shop scheduling problem. In our approach, initial population is created in an agent-based parallel way then an agent-based method is used to parallelize genetic algorithm. Experimental results showed that the proposed approach enhances the performance.
Comparison of Dynamic Scheduling Techniques in Flexible Manufacturing SystemIJERA Editor
Scheduling is an important tool in the manufacturing area since productivity is inherently linked to how well the resources are used to increase efficiency and reduce waste. The present article analyzes and provides comparison of modern techniques used for solving dynamic scheduling problem in flexible manufacturing system. These techniques are often impractical in dynamic real world environments where there are complex constraints and a variety of unexpected disruptions. This paper defines the modern techniques of dynamic scheduling and provides a literature survey of scheduling which are presented in recent few years. The principles of several dynamic scheduling techniques, namely dispatching rules, heuristics, genetic algorithms and artificial intelligence techniques are describe in details and comparison of their potential.
Multi objective genetic algorithm for regression testing reduction eSAT Journals
Abstract Location based authentication is a new direction in development of authentication techniques in the area of security. In this paper, the geographical position of user is an important attribute for authentication of user. It provides strong authentication as a location characteristic can never be stolen or spoofed. As an effective and popular means for privacy protection data hiding in encrypted image is proposed. In our application we are providing secure message passing facilities for this OTP (One Time Password) and Steganoghaphy techniques are used. This technique is relatively new approach towards information security. Keywords: Location based authentication, GPS device, Image encryption, Cryptography, Steganography, and OTP
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
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.
A Non-Revisiting Genetic Algorithm for Optimizing Numeric Multi-Dimensional F...ijcsa
Genetic Algorithm (GA) is a robust and popular stochastic optimization algorithm for large and complex search spaces. The major shortcomings of Genetic Algorithms are premature convergence and revisits to individual solutions in the search space. In other words, Genetic algorithm is a revisiting algorithm that escorts to duplicate function evaluations which is a clear wastage of time and computational resources. In this paper, a non-revisiting genetic algorithm with adaptive mutation is proposed for the domain of MultiDimensional numeric function optimization. In this algorithm whenever a revisit occurs, the underlined search point is replaced with a mutated version of the best/random (chosen probabilistically) individual from the GA population. Furthermore, the recommended approach is not using any extra memory resources to avoid revisits. To analyze the influence of the method, the proposed non-revisiting algorithm is evaluated using nine benchmarks functions with two and four dimensions. The performance of the proposed genetic algorithm is superior as contrasted to simple genetic algorithm as confirmed by the experimental results.
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.
A Genetic Algorithm on Optimization Test FunctionsIJMERJOURNAL
ABSTRACT: Genetic Algorithms (GAs) have become increasingly useful over the years for solving combinatorial problems. Though they are generally accepted to be good performers among metaheuristic algorithms, most works have concentrated on the application of the GAs rather than the theoretical justifications. In this paper, we examine and justify the suitability of Genetic Algorithms in solving complex, multi-variable and multi-modal optimization problems. To achieve this, a simple Genetic Algorithm was used to solve four standard complicated optimization test functions, namely Rosenbrock, Schwefel, Rastrigin and Shubert functions. These functions are benchmarks to test the quality of an optimization procedure towards a global optimum. We show that the method has a quicker convergence to the global optima and that the optimal values for the Rosenbrock, Rastrigin, Schwefel and Shubert functions are zero (0), zero (0), -418.9829 and -14.5080 respectively
A large number of techniques has been developed so far to tell the diversity of machine learning. Machine learning is categorized into supervised, unsupervised and reinforcement learning .Every instance in given data-set used by Machine learning algorithms is represented same set of features .On basis of label of instances it is divided into category. In this review paper our main focus is on Supervised, unsupervised learning techniques and its performance parameters.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
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Immunizing Image Classifiers Against Localized Adversary Attacks
Analysis of selection schemes for solving job shop
1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 11 | Nov-2013, Available @ http://www.ijret.org 775
ANALYSIS OF SELECTION SCHEMES FOR SOLVING JOB SHOP
SCHEDULING PROBLEM USING GENETIC ALGORITHM
A.Ranjini 1
, B.S.E.Zoraida 2
1
Research Scholar, Bharathidasan University, Tiruchirappalli, Tamilnadu, India, ranjini.anbu@gmail.com
2
Assistant Professor, Bharathidasan University, Tiruchirappalli, Tamilnadu, India, b.s.e.zoraida@gmail.com
Abstract
Scheduling problems have the standard consideration in the field of manufacturing. Among the various types of scheduling
problems, the job shop scheduling problem is one of the most interesting NP-hard problems. As the job shop scheduling is an
optimization problem, Genetic algorithm was selected to solve it In this study. Selection scheme is one of the important operators
of Genetic algorithm. The choice of selection method to be applied for solving problems has a wide role in the Genetic algorithm
process. The speed of convergence towards the optimum solution for the chosen problem is largely determined by the selection
mechanism used in the Genetic algorithm. Depending upon the selection scheme applied, the population fitness over the
successive generations could be improved. There are various type of selection schemes in genetic algorithm are available, where
each selection scheme has its own feasibility for solving a particular problem. In this study, the selection schemes namely
Stochastic Universal Sampling (SUS), Roulette Wheel Selection (RWS), Rank Based Roulette Wheel Selection (RRWS) and Binary
Tournament Selection (BTS) were chosen for implementation. The characteristics of chosen selection mechanisms of Genetic
algorithm for solving the job shop scheduling problem were analyzed. The Genetic algorithm with four different selection schemes
is tested on instances of 7 benchmark problems of different size. The result shows that the each of the four selection schemes of
Genetic algorithm have been successfully applied to the job shop scheduling problems efficiently and the performance of
Stochastic Universal Sampling selection method is better than all other four selection schemes.
Keywords: Genetic Algorithm, Makespan, Selection schemes
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1. INTRODUCTION
Scheduling is an optimization process intended to make the
best possible use of the limited resources by making suitable
allotment of the said resources over a period of time [5].
There are several techniques that have been applied to solve
the scheduling problems namely time tabling problem, flow
shop scheduling, etc... One important problem of scheduling
is the job-shop scheduling problem (JSSP). It is a famous
problem in the field of industries especially, in manufacturing
companies and transportation companies. Job shop
scheduling is one of the combinatorial optimization
problems, where the set of possible solutions is very large
and the goal is to find the best possible solution.Traditional
methods can be also be used to solve the job shop problem.
But, the time complexity is there with them. This is because,
when the problem size is small, the traditional methods for
solving JSSP are able to explore the entire search state in
order to obtain the optimal solution within reasonable time.
But it is not the case for the most real world problems.
Therefore, a non-traditional method known as “Genetic
Algorithm” can be utilized in the scheduling of the
manufacturing system. It is a very effective algorithm to
search for solutions for an optimization problem. The
solutions are usually optimum solutions or solutions near by
the optimum value for the chosen problem.
A lot of work has been already carried out for solving the job
shop problem. R.Thamilselvan and P.Balasubramanie [1]
introduced three new crossover operators namely Order
Preserving Multipoint Crossover, Unordered Subsequence
Exchange Crossover and Ordered Partially Mapped
Crossover in the Genetic Algorithm for solving the JSSP.
They analyzed the effectiveness of each of the three
crossover operators by testing them on the known benchmark
problems. From their results, it is proved that the Unordered
Subsequence Exchange Crossover operator provides the
remarkable performance than the other two operators.
R.Sivaraj and Dr.T.Ravichandran [2] presented an overview
of Genetic Algorithm and the various selection schemes used
in the Genetic Algorithm. Tamer F.Abdelmaguid [3]
provided a computational study to compare impact of
chromosome representation in Genetic Algorithm for solving
the JSSP. The performance of the Genetic Algorithm under
six different chromosomes representations was presented in
the paper.It is found that the machine-based representation is
capable of achieving the lowest optimality gap, but with the
highest computational time. Omar Al Jadaan,
LakishmiRajamani[4] and C. R. Rao introduced a new
selection method namely Rank Based Roulette Wheel
selection in their work. The result shows that by introducing
this selection scheme in the Genetic Algorithm the gain of
diversity among population is increased and the uncertainty
in selection process is decreased. Kumar Ritwik and Sankha
Deb [5] developed a new encoding scheme for chromosome
representation. The proposed encoding scheme is compared
with other schemes on the basis of the Lamarkian property,
complexity of decoder and memory requirement. The
proposed scheme was compared with the existing operation
based representation. When the number of operations is
2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 11 | Nov-2013, Available @ http://www.ijret.org 776
small, the proposed scheme performs better than the
operations based scheme. But, when the number of
operations is increased, the proposed scheme tends to lose its
effectiveness. S.M.Kamrul, RuhulSarker and David
Cornforth [6] had presented a hybrid Genetic Algorithm for
solving the JSSP. The proposed Genetic Algorithm includes a
heuristic job ordering with the Genetic Algorithm and they
incorporated a new, but simple local search method.
NorainiMohdRazali and John Geraghty [7] presented the
comparison of Genetic Algorithm performance using
different parent selection strategy in solving travelling
salesman problem. Therefore, the selection strategy has
notable impact for the problem using Genetic Algorithm.
This factor is analyzed in this paper.
2. PROBLEM DESCRIPTION
The classical job-shop scheduling problem can be formulated
as follows [1-5]: A set of n jobs and a set of m machines are
given. The n jobs are to be scheduled on the m machines,
where each job is divided into a set of operations. Each
operation is needed to be processed by the required machine
with the fixed processing time. There are several constrains
on jobs and machines:
1. Every job has to be processed on all machines.
2. Each job must visit each machine exactly once.
3. Each machine can process only one job at a time.
4. The processing order of the set of operations for
each job is pre-specified, which is known as
“precedence constraint” or “technology constraint”.
5. There are no precedence constraints among the
operations of different jobs.
6. All operations are not preemptive. That is, each
operation needs to be processed on the required
machine without interruption for the given period of
time.
7. The operations of the same job cannot be processed
concurrently.
8. We assume that there is no machine failure.
9. Neither release times nor due dates are specified.
The maximum completion time of all the jobs is known as
‘Makespan’. The execution sequence of all operations of all
jobs on the given machines is referred as a schedule. A
schedule is said to be feasible schedule only if it satisfies all
the above stated constraints. The objective of the JSSP is to
find a feasible schedule of minimum length, that is, the
schedule must minimize the makespan.
3. GENETIC ALGORITHM
Genetic Algorithms are bio-inspired search algorithms based
on the evolutionary ideas of natural selection and genetics
that are used successfully to solve problems in many different
disciplines. Genetic Algorithm uses the technique that
resembles natural selection in the biological process. Genetic
Algorithm was developed by John Holland, his colleagues,
and his students at the University of Michigan in the 1960s
and the 1970s. Due to the robustness of Genetic Algorithms
on problems of high complexity, it has an increasing number
of applications in the fields of artificial intelligence, numeric
and combinatorial optimization, business, management,
medicine, computer science, engineering etc.
4. GENETIC ALGORITHM FOR JSSP
4.1 Operation based representation
In the scheduling problems, the popular representation is
operation-based representation for the chromosome. In this
study also, the operation based representation is adopted for
implementation. This representation encodes a schedule as a
sequence of operations where each gene stands for one
operation. All operations of the same job are represented by
the same symbol and they are interpreted according to the
order of their occurrence in the chromosome sequence. Using
the representation, each job number occurs m times in the
chromosome. By scanning the chromosome from left to right,
the k-th occurrence of a job number refers to the k-th
operation in the technological sequence of this job.
As in Fig- 1, an example chromosome for 3 X 5 JSSP is
given as [2 2 1 3 1 2 2 3 1 3 3 1] for the three jobs and five
machines problem. As each job consists of five operations,
the job number occurs exactly five times in the chromosome.
The fourth gene represents the first operation of job 3
because number 3 has been occurred at the first time.
Similarly, the sixth gene in the chromosome implies third
operation of job 2.
4.2 Permutation encoding
There are many chromosome encoding methods are
available. Since the permutation encoding is only for
ordering problem, this encoding is applied in this paper.
4.3 Initial population
In this paper, the initial population is created by means of
random permutation of the operation sequence. It is proved
that the initial solution methods affect the speed of
convergence solution and so the better initial solutions might
provide better results.
4.4 Fitness calculation
The fitness function for the JSSP can be defined as fitness =
1/(makespan).
4.5 Selection
The selection strategy determines which of the chromosomes
in the current generation will be used to reproduce offspring
with the hope that the next generation will have higher
fitness. Different selection strategies have different methods
of calculating selection probability. All the differing selection
techniques develop solutions based on the principle of
survival of the fittest. In this paper, selection schemes namely
Stochastic Universal Sampling, Roulette Wheel Selection,
3. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 11 | Nov-2013, Available @ http://www.ijret.org 777
Rank Based Roulette wheel selection and Binary Tournament
selection were implemented.
4.6 Unordered subsequence exchange crossover
The Unordered Subsequence Exchange Crossover (USXX) is
adopted in this work that children inherit subsequences on
each machine as far as possible from parents [1]. Fig- 2
shows the method for performing the Unordered
Subsequence Exchange Crossover and the procedure to do it
is as follows.
Step 1: Choose two parent individual randomly, namely
Parent1 and Parent2.
Step 2: Select random subset of operations (genes) from
Parent1 and copy it into Child1 with the same
context dependent.
Step 3: Starting from the first crossover point from Parent1,
look for elements within the subsequence in Parent2
and remove those from Parent2.
Step 4: The remaining operations of Parent2 are copied into
Child1 so as to maintain their relative ordering.
Step 5: Change the Parents and go to Step 1 to generate
Child2 in the same manner.
4.7 Swap mutation
In this study, the swap mutation is applied. It randomly takes
two positions in a chromosome and then the alleles in those
positions are swapped. Fig -3 shows the procedure for
performing the swap mutation for an example chromosome
for 3 X 4 JSSP.
4.8 Procedure For Genetic Algorithm For JSSP
A simple and basic Genetic Algorithm cycle for solving the
JSSP is shown in Fig- 4 as follows:
5. RESULTS AND DISCUSSION
The implementation work is carried out using Matlab
software. In order to analyze the effectiveness of various
selection schemes in this paper, the following factors are
taken to be measuredfor each of the four selection schemes.
Frequency of occurrence of optimum solution
Fitness Evolution History and
Quality of solution
Eight well known benchmark problems namely LA1, LA5,
LA6, LA7, LA8, LA11, FT10 and LA13 are tested to
measure these factors.
Frequency of occurrence of optimum solution
The frequency of occurrence of optimum solution refers to
the number of occurrences of known optimum solution out of
a number of trial runs. The result obtained for this factor is
given in Table 1.
Table 1: Frequency Of Occurrence Of Optimum Solution
4. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 11 | Nov-2013, Available @ http://www.ijret.org 778
LA1 LA5 LA6 LA7 LA8 LA11 LA13
0
1
2
3
4
5
6
7
8
9
Benchmark Problems
FrequencyOfOccurence
FREQUENCY OF OCCURENCE OF OPTIMUM SOLUTION
SUS
RRWS
RWS
BTS
Fig -5. Frequency of occurrence of optimum solution
The Fig -5 is drawn using the data given in the Table 1. From
this figure, it is known that the Stochastic Universal
Selection(SUS) scheme has the high frequency of occurrence
of optimum solution for the Rank Based Roulette Wheel
Selection (RBWS), Roulette Wheel Selection (RWS) and
Binary Tournament Selection (BTS). The empty spaces
between the bars in the bar stack of a problem shows the zero
frequency.
Fitness evolution history
The fitness evolution history shows the fitness value
calculated for each iteration of the Genetic algorithm cycle. It
is also used to refer the number of iterations that take to reach
the optimum solution.