Swarm Intelligence Algorithms Two Volume Set
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Swarm Intelligence Algorithms Two Volume Set
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Author : Adam Slowik
language : en
Publisher: CRC Press
Release Date : 2021-01-26
Swarm Intelligence Algorithms Two Volume Set written by Adam Slowik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-26 with Computers categories.
Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior of animals within specific communities. This can be described as simple behaviors of individuals along with the mechanisms for sharing knowledge between them, resulting in the complex behavior of the entire community. Examples of such behavior can be found in ant colonies, bee swarms, schools of fish or bird flocks. Swarm intelligence algorithms are used to solve difficult optimization problems for which there are no exact solving methods or the use of such methods is impossible, e.g. due to unacceptable computational time. This set comprises two volumes: Swarm Intelligence Algorithms: A Tutorial and Swarm Intelligence Algorithms: Modifications and Applications. The first volume thoroughly presents the basics of 24 algorithms selected from the entire family of swarm intelligence algorithms. It contains a detailed explanation of how each algorithm works, along with relevant program codes in Matlab and the C ++ programming language, as well as numerical examples illustrating step-by-step how individual algorithms work. The second volume describes selected modifications of these algorithms and presents their practical applications. This book presents 24 swarm algorithms together with their modifications and practical applications. Each chapter is devoted to one algorithm. It contains a short description along with a pseudo-code showing the various stages of its operation. In addition, each chapter contains a description of selected modifications of the algorithm and shows how it can be used to solve a selected practical problem.
Swarm Intelligence Algorithms Two Volume Set
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Author : Adam Slowik
language : en
Publisher: CRC Press
Release Date : 2022-01-30
Swarm Intelligence Algorithms Two Volume Set written by Adam Slowik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-30 with categories.
Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior of animals within specific communities. This can be described as simple behaviors of individuals along with the mechanisms for sharing knowledge between them, resulting in the complex behavior of the entire community. Examples of such behavior can be found in ant colonies, bee swarms, schools of fish or bird flocks. Swarm intelligence algorithms are used to solve difficult optimization problems for which there are no exact solving methods or the use of such methods is impossible, e.g. due to unacceptable computational time. This set comprises two volumes: Swarm Intelligence Algorithms: A Tutorial and Swarm Intelligence Algorithms: Modifications and Applications. The first volume thoroughly presents the basics of 24 algorithms selected from the entire family of swarm intelligence algorithms. It contains a detailed explanation of how each algorithm works, along with relevant program codes in Matlab and the C ++ programming language, as well as numerical examples illustrating step-by-step how individual algorithms work. The second volume describes selected modifications of these algorithms and presents their practical applications. This book presents 24 swarm algorithms together with their modifications and practical applications. Each chapter is devoted to one algorithm. It contains a short description along with a pseudo-code showing the various stages of its operation. In addition, each chapter contains a description of selected modifications of the algorithm and shows how it can be used to solve a selected practical problem.
Advances In Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Springer Nature
Release Date : 2023-07-07
Advances In Swarm Intelligence written by Ying Tan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-07 with Computers categories.
This two-volume set LNCS 13968 and 13969 constitutes the proceedings of the 14th International Conference on Advances in Swarm Intelligence, ICSI 2023, which took place in Shenzhen, China, China, in July 2023. The theme of this year’s conference was “Serving Life with Swarm Intelligence”. The 81 full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized into 12 cohesive sections covering major topics of swarm intelligence research and its development and applications. The papers of the first part cover topics such as: Swarm Intelligence Computing; Swarm Intelligence Optimization Algorithms; Particle Swarm Optimization Algorithms; Genetic Algorithms; Optimization Computing Algorithms; Neural Network Search & Large-Scale Optimization; Multi-objective Optimization.
Advances In Swarm Intelligence Part Ii
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2011-06-06
Advances In Swarm Intelligence Part Ii written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-06 with Computers categories.
The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.
Advances In Swarm Intelligence Part I
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2011-05-31
Advances In Swarm Intelligence Part I written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-31 with Computers categories.
The two-volume set (LNCS 6728 and 6729) constitutes the refereed proceedings of the International Conference on Swarm Intelligence, ICSI 2011, held in Chongqing, China, in June 2011. The 143 revised full papers presented were carefully reviewed and selected from 298 submissions. The papers are organized in topical sections on theoretical analysis of swarm intelligence algorithms, particle swarm optimization, applications of pso algorithms, ant colony optimization algorithms, bee colony algorithms, novel swarm-based optimization algorithms, artificial immune system, differential evolution, neural networks, genetic algorithms, evolutionary computation, fuzzy methods, and hybrid algorithms - for part I. Topics addressed in part II are such as multi-objective optimization algorithms, multi-robot, swarm-robot, and multi-agent systems, data mining methods, machine learning methods, feature selection algorithms, pattern recognition methods, intelligent control, other optimization algorithms and applications, data fusion and swarm intelligence, as well as fish school search - foundations and applications.
Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Control, Robotics and Sensors
Release Date : 2018-06
Swarm Intelligence written by Ying Tan and has been published by Control, Robotics and Sensors this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06 with Technology & Engineering categories.
This book presents the basic principles and current algorithms and methods of well-known swarm intelligence algorithms and efficient improvements from typical particle swarm optimisation (PSO), ant colony optimisation (ACO) and fireworks algorithm (FWA) as well as other swarm intelligence algorithms for swarm robotics.
Handbook Of Swarm Intelligence
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Author : Bijaya Ketan Panigrahi
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-02-04
Handbook Of Swarm Intelligence written by Bijaya Ketan Panigrahi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-04 with Technology & Engineering categories.
From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.
Advances In Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2019-07-18
Advances In Swarm Intelligence written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-18 with Computers categories.
The two-volume set of LNCS 11655 and 11656 constitutes the proceedings of the 10th International Conference on Advances in Swarm Intelligence, ICSI 2019, held in Chiang Mai, Thailand, in June 2019. The total of 82 papers presented in these volumes was carefully reviewed and selected from 179 submissions. The papers were organized in topical sections as follows: Part I: Novel methods and algorithms for optimization; particle swarm optimization; ant colony optimization; fireworks algorithms and brain storm optimization; swarm intelligence algorithms and improvements; genetic algorithm and differential evolution; swarm robotics. Part II: Multi-agent system; multi-objective optimization; neural networks; machine learning; identification and recognition; social computing and knowledge graph; service quality and energy management.
Advances In Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2016-09-05
Advances In Swarm Intelligence written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-05 with Computers categories.
This two-volume set LNCS 9712 and LNCS 9713 constitutes the refereed proceedings of the 7th International Conference on Swarm Intelligence, ICSI 2016, held in Bali, Indonesia, in June 2016. The 130 revised regular papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in 22 cohesive sections covering major topics of swarm intelligence and related areas such as trend and models of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their applications; hybrid search optimization; particle swarm optimization; PSO applications; ant colony optimization; brain storm optimization; fireworks algorithms; multi-objective optimization; large-scale global optimization; biometrics; scheduling and planning; machine learning methods; clustering algorithm; classification; image classification and encryption; data mining; sensor networks and social networks; neural networks; swarm intelligence in management decision making and operations research; robot control; swarm robotics; intelligent energy and communications systems; and intelligent and interactive and tutoring systems.
Advances In Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2019-07-18
Advances In Swarm Intelligence written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-18 with Computers categories.
The two-volume set of LNCS 11655 and 11656 constitutes the proceedings of the 10th International Conference on Advances in Swarm Intelligence, ICSI 2019, held in Chiang Mai, Thailand, in June 2019. The total of 82 papers presented in these volumes was carefully reviewed and selected from 179 submissions. The papers were organized in topical sections as follows: Part I: Novel methods and algorithms for optimization; particle swarm optimization; ant colony optimization; fireworks algorithms and brain storm optimization; swarm intelligence algorithms and improvements; genetic algorithm and differential evolution; swarm robotics. Part II: Multi-agent system; multi-objective optimization; neural networks; machine learning; identification and recognition; social computing and knowledge graph; service quality and energy management.