Evolutionary And Swarm Intelligence Algorithms
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Evolutionary And Swarm Intelligence Algorithms
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Author : Jagdish Chand Bansal
language : en
Publisher: Springer
Release Date : 2018-06-06
Evolutionary And Swarm Intelligence Algorithms written by Jagdish Chand Bansal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-06 with Technology & Engineering categories.
This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
Emerging Research On Swarm Intelligence And Algorithm Optimization
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Author : Shi, Yuhui
language : en
Publisher: IGI Global
Release Date : 2014-07-31
Emerging Research On Swarm Intelligence And Algorithm Optimization written by Shi, Yuhui and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-31 with Computers categories.
Throughout time, scientists have looked to nature in order to understand and model solutions for complex real-world problems. In particular, the study of self-organizing entities, such as social insect populations, presents a new opportunity within the field of artificial intelligence. Emerging Research on Swarm Intelligence and Algorithm Optimization discusses current research analyzing how the collective behavior of decentralized systems in the natural world can be applied to intelligent system design. Discussing the application of swarm principles, optimization techniques, and key algorithms being used in the field, this publication serves as an essential reference for academicians, upper-level students, IT developers, and IT theorists.
Swarm And Evolutionary Computation
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Author : Leszek Rutkowski
language : en
Publisher: Springer
Release Date : 2012-04-15
Swarm And Evolutionary Computation written by Leszek Rutkowski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-15 with Computers categories.
The volume LNCS 7269 constitutes the refereed proceedings of the International Symposium on Swarm Intelligence and Differential Evolution, SIDE 2012, held in Zakopane, Poland, in April/May 2012 in conjunction with the 11th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2012 (proceedings published as two-volume set LNAI 7267 and 7268). The 212 revised full papers presented were carefully reviewed and selected from 483 submissions. The volume is divided into two topical parts: proceedings of the 2012 symposium on swarm intelligence and differential evolution and on evolutionary algorithms and their applications.
Evolutionary Computation Swarm Intelligence
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Author : Fabio Caraffini
language : en
Publisher: MDPI
Release Date : 2020-11-25
Evolutionary Computation Swarm Intelligence written by Fabio Caraffini and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Technology & Engineering categories.
The vast majority of real-world problems can be expressed as an optimisation task by formulating an objective function, also known as cost or fitness function. The most logical methods to optimise such a function when (1) an analytical expression is not available, (2) mathematical hypotheses do not hold, and (3) the dimensionality of the problem or stringent real-time requirements make it infeasible to find an exact solution mathematically are from the field of Evolutionary Computation (EC) and Swarm Intelligence (SI). The latter are broad and still growing subjects in Computer Science in the study of metaheuristic approaches, i.e., those approaches which do not make any assumptions about the problem function, inspired from natural phenomena such as, in the first place, the evolution process and the collaborative behaviours of groups of animals and communities, respectively. This book contains recent advances in the EC and SI fields, covering most themes currently receiving a great deal of attention such as benchmarking and tunning of optimisation algorithms, their algorithm design process, and their application to solve challenging real-world problems to face large-scale domains.
Recent Advances In Swarm Intelligence And Evolutionary Computation
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Author : Xin-She Yang
language : en
Publisher: Springer
Release Date : 2014-12-27
Recent Advances In Swarm Intelligence And Evolutionary Computation written by Xin-She Yang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-27 with Technology & Engineering categories.
This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.
Swarm Intelligence And Evolutionary Computation
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Author : Georgios N. Kouziokas
language : en
Publisher: CRC Press
Release Date : 2023-03-10
Swarm Intelligence And Evolutionary Computation written by Georgios N. Kouziokas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-10 with Computers categories.
The aim of this book is to present and analyse theoretical advances and also emerging practical applications of swarm and evolutionary intelligence. It comprises nine chapters. Chapter 1 provides a theoretical introduction of the computational optimization techniques regarding the gradient-based methods such as steepest descent, conjugate gradient, newton and quasi-Newton methods and also the non-gradient methods such as genetic algorithm and swarm intelligence algorithms. Chapter 2, discusses evolutionary computation techniques and genetic algorithm. Swarm intelligence theory and particle swarm optimization algorithm are reviewed in Chapter 3. Also, several variations of particle swarm optimization algorithm are analysed and explained such as Geometric PSO, PSO with mutation, Chaotic PSO with mutation, multi-objective PSO and Quantum mechanics – based PSO algorithm. Chapter 4 deals with two essential colony bio-inspired algorithms: Ant colony optimization (ACO) and Artificial bee colony (ABC). Chapter 5, presents and analyses Cuckoo search and Bat swarm algorithms and their latest variations. In chapter 6, several other metaheuristic algorithms are discussed such as: Firefly algorithm (FA), Harmony search (HS), Cat swarm optimization (CSO) and their improved algorithm modifications. The latest Bio-Inspired Swarm Algorithms are discussed in chapter 7, such as: Grey Wolf Optimization (GWO) Algorithm, Whale Optimization Algorithm (WOA), Grasshopper Optimization Algorithm (GOA) and other algorithm variations such as binary and chaotic versions. Chapter 8 presents machine learning applications of swarm and evolutionary algorithms. Illustrative real-world examples are presented with real datasets regarding neural network optimization and feature selection, using: genetic algorithm, Geometric PSO, Chaotic Harmony Search, Chaotic Cuckoo Search, and Evolutionary Algorithm and also crime forecasting using swarm optimized SVM. In chapter 9, applications of swarm intelligence on deep long short-term memory (LSTM) networks and Deep Convolutional Neural Networks (CNNs) are discussed, including LSTM hyperparameter tuning and Covid19 diagnosis from chest X-Ray images. The aim of the book is to present and discuss several state-of-theart swarm intelligence and evolutionary algorithms together with their variances and also several illustrative applications on machine learning and deep learning.
Swarm Intelligence And Evolutionary Algorithms In Healthcare And Drug Development
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Author : Sandeep Kumar
language : en
Publisher: CRC Press
Release Date : 2019-11-11
Swarm Intelligence And Evolutionary Algorithms In Healthcare And Drug Development written by Sandeep Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-11 with Computers categories.
Healthcare sector is characterized by difficulty, dynamism and variety. In 21st century, healthcare domain is surrounded by tons of challenges in terms of Disease detection, prevention, high costs, skilled technicians and better infrastructure. In order to handle these challenges, Intelligent Healthcare management technologies are required to play an effective role in improvising patient’s life. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data for various purposes for saving lives, reducing medical operations errors, enhancing efficiency, reducing costs and making the whole world a healthy world. Applying Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development is essential nowadays. The objective of this book is to highlight various Swarm Intelligence and Evolutionary Algorithms techniques for various medical issues in terms of Cancer Diagnosis, Brain Tumor, Diabetic Retinopathy, Heart disease as well as drug design and development. The book will act as one-stop reference for readers to think and explore Swarm Intelligence and Evolutionary Algorithms seriously for real-time patient diagnosis, as the book provides solutions to various complex diseases found critical for medical practitioners to diagnose in real-world. Key Features: Highlights the importance and applications of Swarm Intelligence and Evolutionary Algorithms in Healthcare industry. Elaborates Swarm Intelligence and Evolutionary Algorithms for Cancer Detection. In-depth coverage of computational methodologies, approaches and techniques based on Swarm Intelligence and Evolutionary Algorithms for detecting Brain Tumour including deep learning to optimize brain tumor diagnosis. Provides a strong foundation for Diabetic Retinopathy detection using Swarm and Evolutionary algorithms. Focuses on applying Swarm Intelligence and Evolutionary Algorithms for Heart Disease detection and diagnosis. Comprehensively covers the role of Swarm Intelligence and Evolutionary Algorithms for Drug Design and Discovery. The book will play a significant role for Researchers, Medical Practitioners, Healthcare Professionals and Industrial Healthcare Research and Development wings to conduct advanced research in Healthcare using Swarm Intelligence and Evolutionary Algorithms techniques.
Evolutionary Algorithms Swarm Dynamics And Complex Networks
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Author : Ivan Zelinka
language : en
Publisher: Springer
Release Date : 2017-11-25
Evolutionary Algorithms Swarm Dynamics And Complex Networks written by Ivan Zelinka and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-25 with Technology & Engineering categories.
Evolutionary algorithms constitute a class of well-known algorithms, which are designed based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly based on deterministic principles. Due to this nature, it is challenging to predict and control its performance in solving complex nonlinear problems. Recently, the study of evolutionary dynamics is focused not only on the traditional investigations but also on the understanding and analyzing new principles, with the intention of controlling and utilizing their properties and performances toward more effective real-world applications. In this book, based on many years of intensive research of the authors, is proposing novel ideas about advancing evolutionary dynamics towards new phenomena including many new topics, even the dynamics of equivalent social networks. In fact, it includes more advanced complex networks and incorporates them with the CMLs (coupled map lattices), which are usually used for spatiotemporal complex systems simulation and analysis, based on the observation that chaos in CML can be controlled, so does evolution dynamics. All the chapter authors are, to the best of our knowledge, originators of the ideas mentioned above and researchers on evolutionary algorithms and chaotic dynamics as well as complex networks, who will provide benefits to the readers regarding modern scientific research on related subjects.
Swarm Intelligence
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Author : Russell C. Eberhart
language : en
Publisher: Elsevier
Release Date : 2001-04-11
Swarm Intelligence written by Russell C. Eberhart and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-04-11 with Mathematics categories.
Traditional methods for creating intelligent computational systems have privileged private "internal" cognitive and computational processes. In contrast, Swarm Intelligence argues that human intelligence derives from the interactions of individuals in a social world and further, that this model of intelligence can be effectively applied to artificially intelligent systems. The authors first present the foundations of this new approach through an extensive review of the critical literature in social psychology, cognitive science, and evolutionary computation. They then show in detail how these theories and models apply to a new computational intelligence methodology—particle swarms—which focuses on adaptation as the key behavior of intelligent systems. Drilling down still further, the authors describe the practical benefits of applying particle swarm optimization to a range of engineering problems. Developed by the authors, this algorithm is an extension of cellular automata and provides a powerful optimization, learning, and problem solving method. This important book presents valuable new insights by exploring the boundaries shared by cognitive science, social psychology, artificial life, artificial intelligence, and evolutionary computation and by applying these insights to the solving of difficult engineering problems. Researchers and graduate students in any of these disciplines will find the material intriguing, provocative, and revealing as will the curious and savvy computing professional. * Places particle swarms within the larger context of intelligent adaptive behavior and evolutionary computation. * Describes recent results of experiments with the particle swarm optimization (PSO) algorithm * Includes a basic overview of statistics to ensure readers can properly analyze the results of their own experiments using the algorithm. * Support software which can be downloaded from the publishers website, includes a Java PSO applet, C and Visual Basic source code.
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.