Nature 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 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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  • Author : Xin-She Yang
  • Publisher : Academic Press
  • Pages : 442 pages
  • ISBN : 0128197145
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKNature Inspired Computation and Swarm Intelligence

Nature-Inspired Computation and Swarm Intelligence

Nature-Inspired Computation and Swarm Intelligence
  • Author : Xin-She Yang
  • Publisher : Academic Press
  • Release : 24 April 2020
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

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 : 16 May 2013
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 Optimization Algorithms

Nature-Inspired Optimization Algorithms
  • Author : Xin-She Yang
  • Publisher : Elsevier
  • Release : 17 February 2014
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 Computing and Optimization

Nature-Inspired Computing and Optimization
  • Author : Srikanta Patnaik,Xin-She Yang,Kazumi Nakamatsu
  • Publisher : Springer
  • Release : 07 March 2017
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

Discrete Problems in Nature Inspired Algorithms

Discrete Problems in Nature Inspired Algorithms
  • Author : Anupam Prof. Shukla,Ritu Tiwari
  • Publisher : CRC Press
  • Release : 15 December 2017
GET THIS BOOKDiscrete Problems in Nature Inspired Algorithms

This book includes introduction of several algorithms which are exclusively for graph based problems, namely combinatorial optimization problems, path formation problems, etc. Each chapter includes the introduction of the basic traditional nature inspired algorithm and discussion of the modified version for discrete algorithms including problems pertaining to discussed algorithms.

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 : 09 August 2016
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

Nature-Inspired Computation in Engineering

Nature-Inspired Computation in Engineering
  • Author : Xin-She Yang
  • Publisher : Springer
  • Release : 19 March 2016
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 : 26 November 2019
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

Nature Inspired Computing

Nature Inspired Computing
  • Author : Bijaya Ketan Panigrahi,M. N. Hoda,Vinod Sharma,Shivendra Goel
  • Publisher : Springer
  • Release : 03 October 2017
GET THIS BOOKNature Inspired Computing

This volume comprises the select proceedings of the annual convention of the Computer Society of India. Divided into 10 topical volumes, the proceedings present papers on state-of-the-art research, surveys, and succinct reviews. The volumes cover diverse topics ranging from communications networks to big data analytics, and from system architecture to cyber security. This volume focuses on Nature Inspired Computing. The contents of this book will be useful to researchers and students alike.

Nature-Inspired Computation

Nature-Inspired Computation
  • Author : Mario D'Acunto
  • Publisher : Unknown Publisher
  • Release : 18 May 2021
GET THIS BOOKNature-Inspired Computation

Nature inspired computation is an old idea, first proposed in the early fifties by Alan Turing, one of the founders of computer science. Turing suggested computational models of pattern formation in living systems based on systems of coupled reaction-diffusion equations giving rise to spatial patterns due to self-organization of substances in chemical concentrations. Since the pioneering work by Turing, many optimization algorithms stimulated by real-world features have gained great popularity and impact, thanks to their efficiency in solving nonlinear design

Nature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms
  • Author : Vasuki A
  • Publisher : CRC Press
  • Release : 31 May 2020
GET THIS BOOKNature-Inspired Optimization Algorithms

Nature-Inspired Optimization Algorithms, a comprehensive work on the most popular optimization algorithms based on nature, starts with an overview of optimization going from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of optimization techniques, providing us with simple solutions to complex problems in an effective and adaptive manner. The study of the intelligent survival strategies of animals, birds, and insects in a hostile and ever-changing environment has

Swarm Intelligence Algorithms (Two Volume Set)

Swarm Intelligence Algorithms (Two Volume Set)
  • Author : Adam Slowik
  • Publisher : CRC Press
  • Release : 26 January 2021
GET THIS BOOKSwarm Intelligence Algorithms (Two Volume Set)

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

Clever Algorithms

Clever Algorithms
  • Author : Jason Brownlee
  • Publisher : Jason Brownlee
  • Release : 01 January 2011
GET THIS BOOKClever Algorithms

This book provides a handbook of algorithmic recipes from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence that have been described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described in this book were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and

Nature-Inspired Algorithms and Applied Optimization

Nature-Inspired Algorithms and Applied Optimization
  • Author : Xin-She Yang
  • Publisher : Springer
  • Release : 08 October 2017
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

Nature Inspired Computing for Wireless Sensor Networks

Nature Inspired Computing for Wireless Sensor Networks
  • Author : Debashis De,Amartya Mukherjee,Santosh Kumar Das,Nilanjan Dey
  • Publisher : Springer
  • Release : 02 February 2020
GET THIS BOOKNature Inspired Computing for Wireless Sensor Networks

This book presents nature inspired computing applications for the wireless sensor network (WSN). Although the use of WSN is increasing rapidly, it has a number of limitations in the context of battery issue, distraction, low communication speed, and security. This means there is a need for innovative intelligent algorithms to address these issues.The book is divided into three sections and also includes an introductory chapter providing an overview of WSN and its various applications and algorithms as well as