Nature Inspired Computation and Swarm Intelligence

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  • Publisher : Academic Press
  • Release : 24 April 2020
  • ISBN : 9780128197141
  • Page : 442 pages
  • Rating : 4.5/5 from 103 voters

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Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others

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Nature-Inspired Computation and Swarm Intelligence

Nature-Inspired Computation and Swarm Intelligence
  • Author : Xin-She Yang
  • Publisher : Academic Press
  • Release Date : 2020-04-24
  • ISBN : 9780128197141
GET THIS BOOKNature-Inspired Computation and Swarm Intelligence

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired

Nature-Inspired Computing and Optimization

Nature-Inspired Computing and Optimization
  • Author : Srikanta Patnaik,Xin-She Yang,Kazumi Nakamatsu
  • Publisher : Springer
  • Release Date : 2017-03-07
  • ISBN : 9783319509204
GET THIS BOOKNature-Inspired Computing and Optimization

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from

Swarm Intelligence and Bio-Inspired Computation

Swarm Intelligence and Bio-Inspired Computation
  • Author : Xin-She Yang,Zhihua Cui,Renbin Xiao,Amir Hossein Gandomi,Mehmet Karamanoglu
  • Publisher : Newnes
  • Release Date : 2013-05-16
  • ISBN : 9780124051775
GET THIS BOOKSwarm Intelligence and Bio-Inspired Computation

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses

Nature-Inspired Computation in Data Mining and Machine Learning

Nature-Inspired Computation in Data Mining and Machine Learning
  • Author : Xin-She Yang,Xing-Shi He
  • Publisher : Springer Nature
  • Release Date : 2019-09-03
  • ISBN : 9783030285531
GET THIS BOOKNature-Inspired Computation in Data Mining and Machine Learning

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning

Nature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms
  • Author : Xin-She Yang
  • Publisher : Elsevier
  • Release Date : 2014-02-17
  • ISBN : 9780124167452
GET THIS BOOKNature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as

Nature-Inspired Computation in Engineering

Nature-Inspired Computation in Engineering
  • Author : Xin-She Yang
  • Publisher : Springer
  • Release Date : 2016-03-19
  • ISBN : 9783319302355
GET THIS BOOKNature-Inspired Computation in Engineering

This timely review book summarizes the state-of-the-art developments in nature-inspired optimization algorithms and their applications in engineering. Algorithms and topics include the overview and history of nature-inspired algorithms, discrete firefly algorithm, discrete cuckoo search, plant propagation algorithm, parameter-free bat algorithm, gravitational search, biogeography-based algorithm, differential evolution, particle swarm optimization and others. Applications include vehicle routing, swarming robots, discrete and combinatorial optimization, clustering of wireless sensor networks, cell formation, economic load dispatch, metamodeling, surrogated-assisted cooperative co-evolution, data fitting and reverse engineering

Nature Inspired Computing for Data Science

Nature Inspired Computing for Data Science
  • Author : Minakhi Rout,Jitendra Kumar Rout,Himansu Das
  • Publisher : Springer Nature
  • Release Date : 2019-11-26
  • ISBN : 9783030338206
GET THIS BOOKNature Inspired Computing for Data Science

This book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and

Applied Optimization and Swarm Intelligence

Applied Optimization and Swarm Intelligence
  • Author : Eneko Osaba,Xin-She Yang
  • Publisher : Springer Nature
  • Release Date : 2021-05-17
  • ISBN : 9789811606625
GET THIS BOOKApplied Optimization and Swarm Intelligence

This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers,

Recent Advances in Swarm Intelligence and Evolutionary Computation

Recent Advances in Swarm Intelligence and Evolutionary Computation
  • Author : Xin-She Yang
  • Publisher : Springer
  • Release Date : 2014-12-27
  • ISBN : 9783319138268
GET THIS BOOKRecent Advances in Swarm Intelligence and Evolutionary Computation

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

Nature-Inspired Computation and Swarm Intelligence

Nature-Inspired Computation and Swarm Intelligence
  • Author : Xin-She Yang
  • Publisher : Academic Press
  • Release Date : 2020-04-09
  • ISBN : 9780128226094
GET THIS BOOKNature-Inspired Computation and Swarm Intelligence

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications
  • Author : Modestus O. Okwu,Lagouge K. Tartibu
  • Publisher : Springer Nature
  • Release Date : 2020-11-13
  • ISBN : 9783030611118
GET THIS BOOKMetaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm,

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release Date : 2016-07-26
  • ISBN : 9781522507895
GET THIS BOOKNature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating

Handbook of Research on Soft Computing and Nature-Inspired Algorithms

Handbook of Research on Soft Computing and Nature-Inspired Algorithms
  • Author : Shandilya, Shishir K.,Shandilya, Smita,Deep, Kusum,Nagar, Atulya K.
  • Publisher : IGI Global
  • Release Date : 2017-03-10
  • ISBN : 9781522521297
GET THIS BOOKHandbook of Research on Soft Computing and Nature-Inspired Algorithms

Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving,

Nature-Inspired Algorithms and Applied Optimization

Nature-Inspired Algorithms and Applied Optimization
  • Author : Xin-She Yang
  • Publisher : Springer
  • Release Date : 2017-10-08
  • ISBN : 9783319676692
GET THIS BOOKNature-Inspired Algorithms and Applied Optimization

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve

Bio-Inspired Computation and Applications in Image Processing

Bio-Inspired Computation and Applications in Image Processing
  • Author : Xin-She Yang,João Paulo Papa
  • Publisher : Academic Press
  • Release Date : 2016-08-09
  • ISBN : 9780128045374
GET THIS BOOKBio-Inspired Computation and Applications in Image Processing

Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in the field. In addition to documenting state-of-the-art developments, this book also discusses future research trends in bio-inspired computation, helping researchers establish new research avenues to pursue. Reviews the latest developments in bio-inspired computation in image