Computational Intelligence is the study of the design of intelligent agents. An agent is something that
react according to an environment—it does something. Agents includes worms, dogs, thermostats, airplanes,
humans, and society. The purpose of computational intelligence is to understand the principles that make
intelligent behavior possible, in real or artificial systems. Techniques of Computational Intelligence are
designed to model the aspects of biological intelligence. These paradigms include that exhibit an ability to
learn or adapt to new situations,to generalize, abstract, learn and associate. This paper gives review of
comparison between computational intelligence paradigms in Wireless Sensor Network and Finally,a short
conclusion is provided.
A SOFTWARE AGENT FRAMEWORK TO OVERCOME MALICIOUS HOST THREATS AND UNCONTROLLE...ijait
An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. Enormous number of researches is going on by comparing the functional similarities of the Human Immune System for making the agents more adaptable in regard with
security. In this research work, the functional similarities of Human Nervous system are given to the agents by proposing an agent-based framework where the agents can adapt themselves from one of the threats, the malicious host attack. The agents become aware of the malicious hosts’ attack by learning and coordination is maintained by a Co-Agent to make this system work successfully. The concept of learning and coordination are taken from the Human Nervous system functionality. This system has shown a better functioning in maintaining the system performance by making the agents aware of malicious hosts and by producing limited number of clones.
Study on Different Human Emotions Using Back Propagation Methodijiert bestjournal
With fast evolving technology,Cognitive Science plays a vital role in our day-to-day life. Cognitive science is summed up as the study of mind based on scientific methods. It is al l about the sum of all interdisciplinary like philosophy,psychology,linguistics,artificial intelligence,robot ics,and neuroscience. In this paper,I focused on the facial expressions or emotions of human being as it has an impor tant role in interpersonal relations. Without verb communication,one can imagine the mood of a person by expressions. In this method,we use back propagation neural network for implementation. It is an information proce ssing system that has been developed as a generalization of the mathematical model of human recognition.
Smart Brain Wave Sensor for Paralyzed- A Real Time ImplementationSiraj Ahmed
ABSTRACT
As the title of the paper indicates about brainwaves and its uses for various applications based on their frequencies and different parameters which can be implemented as real time application with the title a smart brain wave sensor system for paralyzed patients. Brain wave sensing is to detect a person's mental status. The purpose of brain wave sensing is to give exact treatment to paralyzed patients. The data or signal is obtained from the brainwaves sensing band. This data are converted as object files using Visual Basics. The processed data is further sent to Arduino which has the human's behavioral aspects like emotions, sensations, feelings, and desires. The proposed device can sense human brainwaves and detect the percentage of paralysis that the person is suffering. The advantage of this paper is to give a real-time smart sensor device for paralyzed patients with paralysis percentage for their exact treatment.
Keywords:-Brainwave sensor, BMI, Brain scan, EEG, MCH.
The technologies of ai used in different corporate worldEr. rahul abhishek
Artificial intelligence (AI) is making its way back into the mainstream of corporate technology, this time at the core of business systems which are providing competitive advantage in all sorts of industries, including electronics, manufacturing, software, medicine, entertainment, engineering and communications, designed to leverage the capabilities of humans rather than replace them, today’s AI technology enables an extraordinary array of applications that forge new connections among people, computers, knowledge, and the physical world. Some AI enabled applications are information distribution and retrieval, database mining, product design, manufacturing, inspection, training, user support, surgical planning, resource scheduling, and complex resource management.
ANALYSIS OF SYSTEM ON CHIP DESIGN USING ARTIFICIAL INTELLIGENCEijesajournal
Automation is a powerful word that lies everywhere. It shows that without automation, application will not get developed. In a semiconductor industry, artificial intelligence played a vital role for implementing the chip based design through automation .The main advantage of applying the machine learning & deep learning technique is to improve the implementation rate based upon the capability of the society. The main objective of the proposed system is to apply the deep learning using data driven approach for controlling the system. Thus leads to a improvement in design, delay ,speed of operation & costs. Through this system, huge volume of data’s that are generated by the system will also get control.
ON SOFT COMPUTING TECHNIQUES IN VARIOUS AREAScscpconf
Soft Computing refers to the science of reasoning, thinking and deduction that recognizes and uses the real world phenomena of grouping, memberships, and classification of various quantities under study. As such, it is an extension of natural heuristics and capable of dealing with complex systems because it does not require strict mathematical definitions and
distinctions for the system components. It differs from hard computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role modelfor soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The main techniques in soft computing are evolutionary computing, artificial neural networks, and fuzzy logic and Bayesian statistics. Each technique can be used separately, but a powerful advantage of soft computing is the complementary nature of the techniques. Used together they can produce solutions to problems that are too complex or
inherently noisy to tackle with conventional mathematical methods. The applications of soft computing have proved two main advantages. First, it made solving nonlinear problems, in
which mathematical models are not available, possible. Second, it introduced the human knowledge such as cognition,
ecognition, understanding, learning, and others into the fields of
computing. This resulted in the possibility of constructing intelligent systems such as autonomous self-tuning systems, and automated designed systems. This paper highlights various areas of soft computing techniques.
A SOFTWARE AGENT FRAMEWORK TO OVERCOME MALICIOUS HOST THREATS AND UNCONTROLLE...ijait
An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. Enormous number of researches is going on by comparing the functional similarities of the Human Immune System for making the agents more adaptable in regard with
security. In this research work, the functional similarities of Human Nervous system are given to the agents by proposing an agent-based framework where the agents can adapt themselves from one of the threats, the malicious host attack. The agents become aware of the malicious hosts’ attack by learning and coordination is maintained by a Co-Agent to make this system work successfully. The concept of learning and coordination are taken from the Human Nervous system functionality. This system has shown a better functioning in maintaining the system performance by making the agents aware of malicious hosts and by producing limited number of clones.
Study on Different Human Emotions Using Back Propagation Methodijiert bestjournal
With fast evolving technology,Cognitive Science plays a vital role in our day-to-day life. Cognitive science is summed up as the study of mind based on scientific methods. It is al l about the sum of all interdisciplinary like philosophy,psychology,linguistics,artificial intelligence,robot ics,and neuroscience. In this paper,I focused on the facial expressions or emotions of human being as it has an impor tant role in interpersonal relations. Without verb communication,one can imagine the mood of a person by expressions. In this method,we use back propagation neural network for implementation. It is an information proce ssing system that has been developed as a generalization of the mathematical model of human recognition.
Smart Brain Wave Sensor for Paralyzed- A Real Time ImplementationSiraj Ahmed
ABSTRACT
As the title of the paper indicates about brainwaves and its uses for various applications based on their frequencies and different parameters which can be implemented as real time application with the title a smart brain wave sensor system for paralyzed patients. Brain wave sensing is to detect a person's mental status. The purpose of brain wave sensing is to give exact treatment to paralyzed patients. The data or signal is obtained from the brainwaves sensing band. This data are converted as object files using Visual Basics. The processed data is further sent to Arduino which has the human's behavioral aspects like emotions, sensations, feelings, and desires. The proposed device can sense human brainwaves and detect the percentage of paralysis that the person is suffering. The advantage of this paper is to give a real-time smart sensor device for paralyzed patients with paralysis percentage for their exact treatment.
Keywords:-Brainwave sensor, BMI, Brain scan, EEG, MCH.
The technologies of ai used in different corporate worldEr. rahul abhishek
Artificial intelligence (AI) is making its way back into the mainstream of corporate technology, this time at the core of business systems which are providing competitive advantage in all sorts of industries, including electronics, manufacturing, software, medicine, entertainment, engineering and communications, designed to leverage the capabilities of humans rather than replace them, today’s AI technology enables an extraordinary array of applications that forge new connections among people, computers, knowledge, and the physical world. Some AI enabled applications are information distribution and retrieval, database mining, product design, manufacturing, inspection, training, user support, surgical planning, resource scheduling, and complex resource management.
ANALYSIS OF SYSTEM ON CHIP DESIGN USING ARTIFICIAL INTELLIGENCEijesajournal
Automation is a powerful word that lies everywhere. It shows that without automation, application will not get developed. In a semiconductor industry, artificial intelligence played a vital role for implementing the chip based design through automation .The main advantage of applying the machine learning & deep learning technique is to improve the implementation rate based upon the capability of the society. The main objective of the proposed system is to apply the deep learning using data driven approach for controlling the system. Thus leads to a improvement in design, delay ,speed of operation & costs. Through this system, huge volume of data’s that are generated by the system will also get control.
ON SOFT COMPUTING TECHNIQUES IN VARIOUS AREAScscpconf
Soft Computing refers to the science of reasoning, thinking and deduction that recognizes and uses the real world phenomena of grouping, memberships, and classification of various quantities under study. As such, it is an extension of natural heuristics and capable of dealing with complex systems because it does not require strict mathematical definitions and
distinctions for the system components. It differs from hard computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role modelfor soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The main techniques in soft computing are evolutionary computing, artificial neural networks, and fuzzy logic and Bayesian statistics. Each technique can be used separately, but a powerful advantage of soft computing is the complementary nature of the techniques. Used together they can produce solutions to problems that are too complex or
inherently noisy to tackle with conventional mathematical methods. The applications of soft computing have proved two main advantages. First, it made solving nonlinear problems, in
which mathematical models are not available, possible. Second, it introduced the human knowledge such as cognition,
ecognition, understanding, learning, and others into the fields of
computing. This resulted in the possibility of constructing intelligent systems such as autonomous self-tuning systems, and automated designed systems. This paper highlights various areas of soft computing techniques.
With the surge in modern research focus towards Pervasive Computing, lot of techniques and challenges
needs to be addressed so as to effectively create smart spaces and achieve miniaturization. In the process of
scaling down to compact devices, the real things to ponder upon are the Information Retrieval challenges.
In this work, we discuss the aspects of multimedia which makes information access challenging. An
Example Pattern Recognition scenario is presented and the mathematical techniques that can be used to
model uncertainty are also presented for developing a system that can sense, compute and communicate in
a way that can make human life easy with smart objects assisting from around his surroundings.
Applying Soft Computing Techniques in Information RetrievalIJAEMSJORNAL
There is plethora of information available over the internet on daily basis and to retrieve meaningful effective information using usual IR methods is becoming a cumbersome task. Hence this paper summarizes the different soft computing techniques available that can be applied to information retrieval systems to improve its efficiency in acquiring knowledge related to a user’s query.
Observer/Controller and Ontology/Rule-based Architecture:
A Design Approach for Context-aware Pervasive Computing Systems.
By:
Amina HAMEURLAINE
January 21st, 2016
University of Constantine 2 -Abdelhamid Mehri
Faculty of New Technologies of Information and Communication
Department of Computer Sciences and Applications
MISC Laboratory
Principle of soft computing.
Soft computing.
Goals of soft computing.
Problem solving techniques.
Hard computing v/s soft computing.
Techniques in soft computing.
Advantages of soft computing.
Applications of soft computing.
The Dawn of the Age of Artificially Intelligent NeuroprostheticsSagar Hingal
A summary or an overview of the existing technologies that encapsulate the concepts of NeuroScience and Bio-Technology using the enhanced methods of Artificial-intelligence.
In this review paper, there are several case studies and methodologies of implementations of neuroprosthetics as well as how A.I (Artificial Intelligence) is evolved over the period of time and what is next on the future.....
A brief survey of approaches to using cognitive science artificial intelligence to achieve goals in both the cognitive science and artificial intelligence fields.
AI & Cognitive Computing are some of the most popular business an technical words out there. It is critical to get the basic understanding of Cognitive Computing, which helps us appreciate the technical possibilities and business benefits of the technology.
My presentation gives a brief overview about soft computing and it's concepts. Such as..Neural networks, Machine learning, Artificial Intelligence etc...
With the surge in modern research focus towards Pervasive Computing, lot of techniques and challenges
needs to be addressed so as to effectively create smart spaces and achieve miniaturization. In the process of
scaling down to compact devices, the real things to ponder upon are the Information Retrieval challenges.
In this work, we discuss the aspects of multimedia which makes information access challenging. An
Example Pattern Recognition scenario is presented and the mathematical techniques that can be used to
model uncertainty are also presented for developing a system that can sense, compute and communicate in
a way that can make human life easy with smart objects assisting from around his surroundings.
Applying Soft Computing Techniques in Information RetrievalIJAEMSJORNAL
There is plethora of information available over the internet on daily basis and to retrieve meaningful effective information using usual IR methods is becoming a cumbersome task. Hence this paper summarizes the different soft computing techniques available that can be applied to information retrieval systems to improve its efficiency in acquiring knowledge related to a user’s query.
Observer/Controller and Ontology/Rule-based Architecture:
A Design Approach for Context-aware Pervasive Computing Systems.
By:
Amina HAMEURLAINE
January 21st, 2016
University of Constantine 2 -Abdelhamid Mehri
Faculty of New Technologies of Information and Communication
Department of Computer Sciences and Applications
MISC Laboratory
Principle of soft computing.
Soft computing.
Goals of soft computing.
Problem solving techniques.
Hard computing v/s soft computing.
Techniques in soft computing.
Advantages of soft computing.
Applications of soft computing.
The Dawn of the Age of Artificially Intelligent NeuroprostheticsSagar Hingal
A summary or an overview of the existing technologies that encapsulate the concepts of NeuroScience and Bio-Technology using the enhanced methods of Artificial-intelligence.
In this review paper, there are several case studies and methodologies of implementations of neuroprosthetics as well as how A.I (Artificial Intelligence) is evolved over the period of time and what is next on the future.....
A brief survey of approaches to using cognitive science artificial intelligence to achieve goals in both the cognitive science and artificial intelligence fields.
AI & Cognitive Computing are some of the most popular business an technical words out there. It is critical to get the basic understanding of Cognitive Computing, which helps us appreciate the technical possibilities and business benefits of the technology.
My presentation gives a brief overview about soft computing and it's concepts. Such as..Neural networks, Machine learning, Artificial Intelligence etc...
Introduction
Background
WSN Design Issues: MAC Protocols, Routing Protocols, Transport Protocols
Performance Modeling of WSNs: Performance Metrics, Basic Models, Network Models
Case Study: Simple Computation of the System Life Span
Practical Example.
Slides from our latest webinar "Top 5 Security Threats Facing Businesses Today." Whether or not they are truly the top 5 most dangerous threats may be debatable but the threat they pose to a businesses network are not. Enjoy!
Analyze the Customer Requirements
Characterize the Existing Network and Sites
Design the Network Topology and Solutions
Design a Network Topology
Design a Model for Network Layer Addressing and Naming
Select the Switching and Routing Protocols
Network Security Design
Network Management Design
Optimize the Network Design
Select Technologies and Devices
Test the Network Design
Document the Network Design
Ambient intelligence is an emerging discipline that brings intelligence to our everyday environments and makes those environments sensitive to us. Ambient intelligence (AmI) research builds upon advances in sensors and sensor networks, pervasive computing, and artificial intelligence.
Proactive Intelligent Home System Using Contextual Information and Neural Net...IJERA Editor
Nowadays, cities around the world intend to use information technology to improve the lives of their citizens.
Future smart cities will incorporate digital data and technology to interact differently with their human
inhabitants.
Among the key component of a smart city, we find the smart home component. It is an autonomic environment
that can provide various smart services by considering the user’s context information. Several methods are used
in context-aware system to provide such services. In this paper, we propose an approach to offer the most
relevant services to the user according to any significant change of his context environment. The proposed
approach is based on the use of context history information together with user profiling and machine learning
techniques. Experimentations show that the proposed solution can efficiently provide the most useful services to
the user in an intelligent home environment.
Soft computing is an umbrella term used to describe types of algorithms that produce approximate solutions to unsolvable high-level problems in computer science.
Artificial Intelligence (AI) has revolutionized in information technology.AI is a subfield of computer science that includes the creation of intelligent machines and software that work and react like human beings. AI and its Applications gets used in various fields of life of humans as expert system solve the complex problems in various areas as science, engineering, business, medicine, video games and Advertising. But “Do any traffic lights use Artificial Intelligence??”, I thought a lot of this when waiting in a red light. This paper gives an overview of Artificial Intelligence and its applications used in human life. This will explore the current use of Artificial Intelligence technologies in Network Intrusion for protecting computer and communication networks from intruders, in the medical area-medicine, to improve hospital inpatient care, for medical image classification, in the accounting databases to mitigate the problems of it, in the computer games, and in Advertising. Also, it will show artificial intelligence principle and how they were applying in traffic signal control, how they solve some traffic problem in actual. This paper gives an introduction to a self-learning system based on RBF neural network and how the system can simulate the traffic police’s experience. This paper is focusing on how to evaluate the effect of the control with the changing of the traffic and adjust the signal with the different techniques of Artificial Intelligence.
Informative Centers' Intelligent Agent Based Model - a preliminary studytulipbiru64
Paper presented by Mazwani Ayu Mazlan, Jannatul Iza Ahmad Kamal, Intan Nurbaizura Zainuddin and Jafalizan Md. Jali at the 4th PERPUN International Conference 2015: Information Revolution, 11-12th August 2015 at Avillion Legacy Hotel, Melaka.
Introduction–Definition - Future of Artificial Intelligence – Characteristics of Intelligent Agents– Typical Intelligent Agents – Problem Solving Approach to Typical AI problems.
Useful and Effectiveness of Multi Agent Systemijtsrd
A multi agent system MAS or self cooperating system is a computerized system organized of multiple interacting intelligent agents. The problems that are difficult to solve for an individual agent or a monolithic system can be solved by multi agent system easily. MAS is a loosely coupled of software agents' network that interact to solve problems that are beyond the individual capacities or knowledge of each software agent. Distributed systems with a group of intelligent agents that communicate with other agents to achieve goals are directed by their masters. MAS group aims to develop new theory and computational models of higher order social cognition between people and computer systems by producing their abilities to reason about one another automatically. More specifically, multi agent control systems are fundamental parts of a wide range of safety critical engineering systems, and are commonly found in aerospace, traffic control, chemical process, power generation and distribution, flexible manufacturing, chemical processes, power generation and distribution, flexible manufacturing, robotic system design and self assembly structures. Moe Myint Myint ""Useful and Effectiveness of Multi-Agent System"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23036.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23036/useful-and-effectiveness-of-multi-agent-system/moe-myint-myint
Towards the Intelligent Internet of EverythingRECAP Project
In this presentation, Prof. Theo Lynn (DCU) was talking about observations on Multi-disciplinary Challenges in Intelligent Systems Research, at the RECAP consortium meeting in Dublin, Ireland on 06 November 2018.
UBIQUITOUS COMPUTING Its Paradigm, Systems & Middlewarevivatechijri
This paper offers a survey of ubiquitous computing research which is the developing a scope that
gears communication technologies into routine life accomplishments. This study paper affords a types of the
studies that extents at the ubiquitous computing exemplar. In this paper, we present collective structure principles
of ubiquitous systems and scrutinize important developments in context-conscious ubiquitous structures. In toting,
this studies work affords a novel structure of ubiquitous computing system and an evaluation of sensors needed
for applications in ubiquitous computing. The goal of this studies work are 3-fold: i) help as a parameter for
researchers who're first-hand to ubiquitous computing and want to subsidize to this research expanse, ii) provide
a unique machine architecture for ubiquitous computing system, and iii) offer auxiliary studies ways necessary
for exceptional-of-provider assertion of ubiquitous computing..
An Examination of Effectuation Dimension as Financing Practice of Small and M...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Does Goods and Services Tax (GST) Leads to Indian Economic Development?iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Childhood Factors that influence success in later lifeiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Emotional Intelligence and Work Performance Relationship: A Study on Sales Pe...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Customer’s Acceptance of Internet Banking in Dubaiiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Study of Employee Satisfaction relating to Job Security & Working Hours amo...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Consumer Perspectives on Brand Preference: A Choice Based Model Approachiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Student`S Approach towards Social Network Sitesiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Broadcast Management in Nigeria: The systems approach as an imperativeiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Study on Retailer’s Perception on Soya Products with Special Reference to T...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Study Factors Influence on Organisation Citizenship Behaviour in Corporate ...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Consumers’ Behaviour on Sony Xperia: A Case Study on Bangladeshiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Design of a Balanced Scorecard on Nonprofit Organizations (Study on Yayasan P...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Public Sector Reforms and Outsourcing Services in Nigeria: An Empirical Evalu...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Media Innovations and its Impact on Brand awareness & Considerationiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Customer experience in supermarkets and hypermarkets – A comparative studyiosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Social Media and Small Businesses: A Combinational Strategic Approach under t...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Secretarial Performance and the Gender Question (A Study of Selected Tertiary...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Implementation of Quality Management principles at Zimbabwe Open University (...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Organizational Conflicts Management In Selected Organizaions In Lagos State, ...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
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.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
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
adversary training.
Comparative Analysis of Computational Intelligence Paradigms in WSN: Review
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 6, Ver. II (Nov – Dec. 2015), PP 44-49
www.iosrjournals.org
DOI: 10.9790/0661-17624449 www.iosrjournals.org 44 | Page
Comparative Analysis of Computational Intelligence Paradigms
in WSN: Review
Sonal Chawla, Neetika Goswami
M.Tech Scholar, CSE Deptt., P.D.M. College of Engineering Bahadurgarh
M.Tech Scholar, CSE Deptt., P.D.M. College of Engineering Bahadurgarh
Abstract: Computational Intelligence is the study of the design of intelligent agents. An agent is something that
react according to an environment—it does something. Agents includes worms, dogs, thermostats, airplanes,
humans, and society. The purpose of computational intelligence is to understand the principles that make
intelligent behavior possible, in real or artificial systems. Techniques of Computational Intelligence are
designed to model the aspects of biological intelligence. These paradigms include that exhibit an ability to
learn or adapt to new situations,to generalize, abstract, learn and associate. This paper gives review of
comparison between computational intelligence paradigms in Wireless Sensor Network and Finally,a short
conclusion is provided.
Keywords: Computational Intelligence, Computational Intelligence Techniques, Swarm Intelligence ,Genetic
Algorithm, Artificial Neural Network.
I. Introduction
Computational Intelligence is a technique which is inspired from nature. It is used for complex
problem solutions.Computational Intelligence is used to make systems which can work in real time.
Computational intelligence is different from artificial intelligence. In artificial intelligence like robots, they are
used to do predefined things like they can place things from one place to another, opening or shutting of the
door etc. All such things are already inserted into the memory of the robot to perform all those tasks. Purpose of
CI is to introduce such intelligence in the system that it can take decisions like humans do, according to an
environment like they can select best solution from a set of available options.
Computational intelligence is defined as “The computational models and tools of intelligence, able of
inputting raw numerical sensory data directly, manage them by exploiting the representational parallelism and
pipelining the problem,generating authentic and timely responses and withstanding high fault liberality” [1].
CI has been a source of providing solutions in various fields. Computational Intelligence techniques
have been successfully employed in a wide range of application areas ,including decision support, genetic
clustering and classification, consumer electronic devices, stock market and other time-series
prediction,combinatorial optimization ,medical, bioinformatics problems and many others.
The rest of this paper is organized as given: Characterstics of Computational Intelligence in Section II.
Applications of Computational Intelligence is discussed in Section III. In Section IV A brief overview on
Computational Intelligence techniques.In Section V in which comparative analysis of computational intelligence
are given and last section VI concludes the work.
II. Characterstics Of CI
The characteristics of Computational Intelligence[2] with the following points:
Adaptation: As these systems are designed to work in real time and can react to different situations
accordingly like node failure or topology change. They are very adaptive so they can adjust to changing
situations
High Computational Speed: As these systems are working on real time so they must be very fast. For that
aim they have high computational speed so that they meet the requirement of real time applications.
Versatility: Versatility is another characteristic of CI. They are very adjustable and can handle highly non-
linear mappings without external help.
Robustness: It imposes little or no necessity on the objective function.
Self Organizing: Due to many reasons network topology gets changed. Self organization is the
characteristic which deals with this problem and also used in the initial stages of network deployment.
Self Learning: In self learning systems are given a set of instructions and rules. System then takes the input
from environment and then on the basis of that input processing is done. On the basis of that processed
information and given set of instructions, system gives output according to real time scenario but that
output was not fed into the memory of that system.
2. Comparative Analysis of Computational Intelligence Paradigms in WSN: Review
DOI: 10.9790/0661-17624449 www.iosrjournals.org 45 | Page
III. Computational Intelligence Applications
CI‟s applications are diverse, including medical diagnosis, robots for hazardous environments, chess
playing, autonomous vehicles, natural language translation systems, and cooperative systems. Rather than
treating each application individually, we abstract important points of such applications to allow us to study
principles behind intelligent reasoning and action. The three application domains of computational intelligence
are:
Autonomous delivery robot: It can roam around a building delivering packages and coffee to people in the
building. This delivery agent requires to be skill to, for example, find paths, assign resources, receive
requests from people, make decisions about priorities, and supply of packages without injuring people or
itself.
Diagnostic assistant: Assistant helps a human troubleshoot problems and suggests repairs or treatments to
rectify the problems. An example is of a medical diagnostician that finds potential diseases, possible tests,
and appropriate treatments based on knowledge of a particular medical domain and a patient‟s symptoms
and history. This assistant needs to be able to explain its reasoning to the person who is carrying out the
tests and rebuilt, as that person is eventually supervise for what they do. The diagnostic assistant must
append valuable value in order to be worth using.
Infobot: One of the best application of computational intelligence can search for users such as company
managers or people off the street. In sequence to do this the infobot should find out, using the user‟s real
language, what data is requested, determine where to find out the information, and gain the information
from the appropriate sources. It then must explain its findings in an appropriate format so that the human
can understand the information found, including what they can infer from the lack of information.
IV. Computational Intelligence Paradigms
Computational Intelligence is the study of the design of intelligent agents. An intelligent agent is a
system that behave intelligently and what it does is appropriate for its circumstances and its goal,flexible to
changing environments and goals, gain from experience, and suitable choices given perceptual limitations and
finite computation.”[2].Better computer systems and improved performance of computational tasks such as
flexibility, adaptability, decentralization and fault tolerance are few important traits of CI.Paradigms of CI are
planned to model the aspects of biological intelligence. CI encompasses paradigms such as artificial neural
networks, reinforcement learning, swarm intelligence, evolutionary algorithms, fuzzy logic and artificial
immune systems.CI has been a source of producing solutions in various fields. Computational Intelligence
techniques have been successfully employed in a wide range of application areas ,including decision support,
genetic clustering and classification, consumer electronic devices, stock market and other time-series prediction,
combinatorial optimization ,medical, bioinformatics problems and many others.The CI paradigms address a
multidisciplinary, rich, and, diverse area of research in a number of applications in various fields. Such as WSN,
digital communications, RF and microwave communication, radars communication, signal processing,
acoustics, power, and lots more.
A. Artificial Neural Networks
Human brain is performing different tasks and working them faster than computers. Design of artificial
neural networks(ANN) is taken from brain‟s neural network. ANNs have abilities of learning, memorizing etc.
Huge numbers of nerve cells (neurons) combine to make a biological neural network. Axon, dendrites and cell
body creates up a neuron. Axon of one neuron join with dendrite of another neuron for communication. In same
way number of neurons gets interconnected. The connection between axon and dendrite is known as synapse.
Fig 1:Features of ANN
Signal moves from axon of one neuron to the dendrite of another neuron.Inside a neuron signal moves
from dendrite to body and then to axon and then axon passes that signal to all connected dendrites. “A signal is
transferred to the axon of a neuron only when the cell “fires”.
FEATURES OF ANN
Adaptive Learning
Self organization
Fault tolerant
3. Comparative Analysis of Computational Intelligence Paradigms in WSN: Review
DOI: 10.9790/0661-17624449 www.iosrjournals.org 46 | Page
A neuron either can inhibit or excite a signal.” [3]. Artificial Neuron is raise on the basis of biological neuron. It
gathers the information from the environment or connected neurons and transmits the information to the
connected neurons only when it is fired. Neural Networks need very high processing and large memory. It
usually supply centralized solutions. Solutions are basically slow in speed. It usually provides centralized
solutions. It is good for data aggregation and fusion [4].Applications of Artificial Neural Network are Diagnosis
of diseases, Speech Recognition,Data mining,Image processing,Robot control,Pattern recognition and
Compression and many others.[5]
B. Genetic Algorithm
Inspired by Charles Darwin‟s theory of evolution: ‟the survival of the fittest”, Genetic Algorithm (GA)
was initiated formally by John Holland in 1970s [6]. GA is an adaptive heuristic search algorithm that models
biological genetic evolution. It displayed to be a robust optimizer that searches among a group of solutions, and
showed flexibility in solving dynamic problems.It has been successfully obtain to many NP-hard problems. The
main challenge in solving a problem with GA is the encoding of the problem into a set of chromosomes; each
representing a solution to the problem. The status of each chromosome is evaluated using a fitness function.
According to their fitness value, crossover 3 and mutation processes are applied on selected
chromosomes. The crossover process produces new solutions, called offspring,by interconnecting parts of two
selected chromosomes. Transmutation changes one or more genetic element in the produced offspring to prevent
being trapped in local minima.Applications of Genetic Algorithm are Data mining, Combinatorial
optimization,Fault diagnosis,Clustering and Scheduling.
Fig 2:Features of Genetic Algorithm
C. Fuzzy Logic
Fuzzy means vague, indistinct or difficult to perceive.Unlike Boolean where values are integer i.e. „1‟
or „0‟, where„1‟ represents true and „0‟ represents false, it (fuzzy) takes continuous values between „0‟ and „1‟.
In fuzzy systems „0‟ represents absolute wrong and „1‟ represents absolute correct and give continuous values
for other conditions.Let‟s take an example of fan, if we are using Boolean system then it would either TURN
ON or TURN OFF the fan,If it is tough or easy, if it is cold or hot. But if we use fuzzy system then it will set the
speed of fan from stop to slow, slow to medium and so on,depending on the value of temperature [6]. Fuzzy
logic is used in optimization, clustering heuristic and routing. The solutions it provides are not optimal. It is
good for security and QoS problems. It usually provides centralized solutions. It is good for data aggregation
and fusion [7].Applications of fuzzy logic are control systems,gear transmission,braking systems in vehicles,
controlling lifts,Home appliance and controlling traffic signals.
Fig 3:Features of Fuzzy Logic
D. Swarm Intelligence
Swarm intelligence is based on the study of swarms that how they live, communicate, forage for food
etc. They have no central control, no direct communication but still they manage to find shortest paths, find
FEATURES OF FUZZY
LOGIC
Put up system Nonlinearity
Deterministic
Performs best even with
small input
Accurate
FEATURES OF GENETIC
ALGORITHM
Solutions to optimization and
search problems.
Good global solutions
4. Comparative Analysis of Computational Intelligence Paradigms in WSN: Review
DOI: 10.9790/0661-17624449 www.iosrjournals.org 47 | Page
foods and manage their resources well. Swarm introduce the large no of insects or other small organized entities,
esp. when they are in motion. Global intelligent behavior to which the individuals are entirely unknown is
emerged due to the local, self-organized and decentralized interaction of swarm‟s agents.
Fig 4:Features of Swarm Intelligence
Swarm intelligence (SI) is one of the aspiring solutions from bioinspired computing for such heuristic
optimization problems e.g. routing Natural examples of SI include ant colony, bird flocking, animal herding,
bacterial growth, fish schooling, drop water, fireflies etc. Examples algorithms under the head of SI are Ant
Colony Optimization (ACO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA),
Intelligent Water Drop (IWD), Charged System Search (CSS) and Stochastic Diffusion Search (SDS) etc.Swarm
intelligence gives effective solutions for routing in the ad-hoc networks.It consumes vast amount of energy on
communication when it send to ants for route discovery. Applications of Swarm Intelligence are Function
approximation, Clustering, Optimization of Mechanical structures, Solving systems of Equations, Routing
optimization and Graph Coloring.
Partial Swarm Optimization: Particle Swarm Optimization (PSO) was developed in 1995 by James
Kennedy, and Russell Eberhart . PSO is a robust stochastic nonlinear- optimization technique based on
movement and intelligence of swarms.It is stimulate from social behavior of bird or fish, where a group of
birds search for food in an area by following the nearest bird to the food. It merge local search methods
with global search methods depending on social interaction between particles to locate the best achieved
position so far. PSO and GA are very similar. Both are population based stochastic optimization that starts
with a group of a randomly generated population. They have fitness values to evaluate their population, and
update the population and search for the optimum with random techniques. However, PSO differs from GA
in that there is no crossover and mutation. PSO particles do not die.They update themselves with the
internal velocity. Finally, the information sharing mechanism in PSO is significantly different. Each particle
is treated as a point in a multi-dimensional space, and modifies its position influenced by two components:
the cognitive component and the social component resulting from neighbor communication.
E. Artificial Immune System
Artificial immune system is basically inspired from natural or real immune system and it models some
aspects of artificial immune system. Natural immune system (NIS) is having a great pattern matching ability. It
is used to differentiate between foreign cells entering the body (antigen or non-self) and the cells belonging to
the body (self). NIS fights the antigens and memorizes their structure for faster future response if they try again
to enter the body. The four models of natural immune system are Classic view, clonal selection theory, danger
theory and network theory. Artificial immune system is use to give security, fault detection, optimization and
abnormality detection.
Immune network models: Immune network models are based on the hypothesis that the immune system
uses an idiotypic network of interconnected B cells - a component of the adaptive immune system - for
antigen recognition. The power of interconnection between two B cells is directly proportional to the
affinity they share. A B cell population has two kinds of sub-populations: the initial population and the
cloned population. The initial subset is produced from raw training data, and the rest are used for antigen
training items. Antigens are randomly choosed from training set and presented to areas of the B cell
network.
In case of successful binding, the B cell is cloned and mutated, leading to a diverse set of antibodies.
When a new B cell is produced, it is added into the network at the closest B cells. If the new cell cannot be
added, it is deleted from the population. If all binds fail, a B cell is produced using the antigen as a template and
is then included into the network.Applications of Artificial Immune System are Pattern Recognition problems,
Classification, Clustering, Anamoly Detection,Computer virus Detection.[8]
FEATURES OF SWARM
INTELLIGENCE
Distributiveapproach
Self organization
Decentralized control
Powerful
optimization tool
5. Comparative Analysis of Computational Intelligence Paradigms in WSN: Review
DOI: 10.9790/0661-17624449 www.iosrjournals.org 48 | Page
Fig 5:Features of Artificial Immune System
V. Comparative Analysis Of CI Paradigms In WSN
The CI paradigms untie the restriction of obstruction by its vast and multiobjective nature. State
variables, no of search points, runtime, target problem, are efficient to compare and analyze CI paradigm
algorithms to solve WSN issues .It can also be applied to a huge amount of fields to give and optimal and solve
the issues of different application fields of CI. Here optimized energy aware routing is approved. These are all
helps to optimize a particular problem. Table 1 shows a comparative analysis of each CI paradigms
algorithms.The important subheads are discussed below.
A. State variables:
Table 1:Comparative Analyis of Computational Intelligence Paradigms in WSN
B. No of search points
Multipoint search is basically used in every CI based algorithms Where the search point gives a
framework to construct an optimal solution of a problem among existing solutions to find the result in optimality
.
C. Solution guarantee.
It usually deals with the efficiency of the algorithm that under what conditions it is working and how
its performance is evaluated based on the computational cost and optimality.
D. Run time
The run time feature of CI based algorithm is the measure of the time taken to compute the job at hand
unlike FL which has short run time due to the fact that it works on initial subset selection from the actual data
and then compute the deterministic results efficiently, all others ANN, AIS, GA and SI have the runtime of long
to medium respectively. Though AIS has more computation then GA but proves to be more optimal in results
then GA. Similarly the distributed and decentralized feature of the SI gives the cutting edge superiority as
optimizer among others for routing in CI paradigm.
FEATURES OF
ARTIFICIAL IMMUNE
SYSTEM
Pattern recognition
problems
Classification
Clustering
Anomaly detection
Computer virus detection
6. Comparative Analysis of Computational Intelligence Paradigms in WSN: Review
DOI: 10.9790/0661-17624449 www.iosrjournals.org 49 | Page
E. Target problem
There are optimization problems the Computational Intelligence focused as combinatorial optimization,
multi-objective optimization, continuous optimization, nonlinear optimization and global optimization. Each
paradigm in Table 1 shows a variation of optimization problems. A continuous optimization and combinatorial
optimization problem varies in respect to their feasibility of available solutions by maximizing and minimizing
of continuous and discrete function values respectively i.e. in continuous optimization an infinite feasible
solutions are available for selection of an
optimal solution, and in combinatorial optimization an optimal solution is selected from a finite number
of solutions .Multiobjective optimization problems deals with the multitudes objectives, which are to be
optimized simultaneously or a trade off exists between the multiple objectives for an optimal solutions.
Nonlinear optimization problems are used to optimize the problems of non linear objective functions. Similarly
the global optimization is responsible for the problems of certain criteria which need to be optimized.
VI. Conclusion
This paper represents the concept of computational intelligence and various applications are given. All
the computational intelligence paradigms are useful in various areas and every day paradigms are modified for
future use. Basically, In this paper we show the comparative analysis of Computational Intelligence techniques
in Wireless Sensor Network to solve the WSN issues. This review paper gives idea about basic computational
intelligence paradigms and comparative analaysis of CI techniques in WSN.
References:
[1] A.konar, computational intelligence: principles, techniques and applications. Springer, 2005.
[2] Anastasi, G., Conti, M., Francesco, D.M, Passarella. A, “Energy Conservation in WSNs: a Survey”, Elsevier Science Publishers
AdHoc Networks, vol.7, No.3 pp. 537-568, May 2009.
[3] P. Stone, M. Veloso, “Team-partitioned, opaque-transition reinforcement learning,” in Proc. 3rd Annual Conf. Autonomous Agents.
[4] Dressler, Self-Organization in Sensor and Actor Networks, John Wiley & Sons, 2007.
[5] P. Stone, M. Veloso, “Team-partitioned, opaque-transition reinforcement learning,” in Proc. 3rd Annual Conf. Autonomous Agents
(AGENTS). Newyork, USA.
[6] Basma Solaiman and Alaa Sheta. Computational Intelligence for Wireless Sensor Networks: Applications and Clustering
Algorithms. ” International Journal of Computer Applications (0975 8887)”:Volume 73 - No. 15, July 2013.
[7] http://www.csee.wvu.edu/classes/cpe521/presentations/System.pdf.
[8] Sajjad Hussain Shah, Kashif Naseer, Wajid Ali, Sohail Jabbar, Abid Ali Minhas. Prolonging the Network Life Time in WSN
through Computational Intelligence: Proceedings of the World Congress on Engineering and Computer Science 2011 Vol I WCECS
2011, October 19-21, 2011, San Francisco, USA.