Evolutionary Computing And Artificial Intelligence

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Introduction To Evolutionary Computing

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Author : Agoston E. Eiben
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14

Introduction To Evolutionary Computing written by Agoston E. Eiben 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 2013-03-14 with Computers categories.

Evolutionary Computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being increasingly widely applied to a variety of problems, ranging from practical applications in industry and commerce to leading-edge scientific research. This book presents the first complete overview of this exciting field aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. To this group the book is valuable because it presents EC as something to be used rather than just studied. Last, but not least, this book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Evolutionary Machine Learning Techniques

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Author : Seyedali Mirjalili
language : en
Publisher: Springer Nature
Release Date : 2019-11-11

Evolutionary Machine Learning Techniques written by Seyedali Mirjalili and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-11 with Technology & Engineering categories.

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.

Artificial Intelligence And Evolutionary Algorithms In Engineering Systems

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Author : L. Padma Suresh
language : en
Publisher: Springer
Release Date : 2014-11-01

Artificial Intelligence And Evolutionary Algorithms In Engineering Systems written by L. Padma Suresh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-01 with Technology & Engineering categories.

The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

Artificial Intelligence And Evolutionary Computations In Engineering Systems

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Author : Subhransu Sekhar Dash
language : en
Publisher: Springer
Release Date : 2018-03-19

Artificial Intelligence And Evolutionary Computations In Engineering Systems written by Subhransu Sekhar Dash and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-19 with Technology & Engineering categories.

The book is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES 2017). The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academia and industry have presented their original work and ideas, information, techniques and applications in the field of communication, computing and power technologies.

Evolutionary Computation In Bioinformatics

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Author : Gary Fogel
language : en
Publisher: Morgan Kaufmann
Release Date : 2003

Evolutionary Computation In Bioinformatics written by Gary Fogel and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.

This book offers a definitive resource that bridges biology and evolutionary computation. The authors have written an introduction to biology and bioinformatics for computer scientists, plus an introduction to evolutionary computation for biologists and for computer scientists unfamiliar with these techniques.

Illustrating Evolutionary Computation With Mathematica

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Author : Christian Jacob
language : en
Publisher: Morgan Kaufmann
Release Date : 2001

Illustrating Evolutionary Computation With Mathematica written by Christian Jacob and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.

Part 1: Fascinating Evolution -- Part 2: Evolutionary Computation -- Part 3: If Darwin was a Programmer -- Part 4: Evolution of Developmental Programs.

Genetic And Evolutionary Computing

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Author : Jeng-Shyang Pan
language : en
Publisher: Springer Nature
Release Date : 2020-03-12

Genetic And Evolutionary Computing written by Jeng-Shyang Pan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-12 with Technology & Engineering categories.

This book gathers papers presented at the 13th International Conference on Genetic and Evolutionary Computing (ICGEC 2019), which was held in Qingdao, China, from 1st to 3rd, November 2019. Since it was established, in 2006, the ICGEC conference series has been devoted to new approaches with a focus on evolutionary computing. Today, it is a forum for the researchers and professionals in all areas of computational intelligence including evolutionary computing, machine learning, soft computing, data mining, multimedia and signal processing, swarm intelligence and security. The book appeals to policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, and other professionals in the learning industry, and further and continuing education.

Evolutionary Computing And Artificial Intelligence

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Author : Fernando Koch
language : en
Publisher: Springer
Release Date : 2019-03-13

Evolutionary Computing And Artificial Intelligence written by Fernando Koch and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-13 with Computers categories.

This Festschrift volume is published in honor of Takao Terano on the occasion of his retirement. Takao Terano is a leading expert in the areas of agent-based modelling, knowledge systems, evolutionary computation, and service science.The contributions in this volume reflect the breadth and impact of his work. The volume contains 12 full papers related to Takao Terano’s research. They deal with various aspects of artificial intelligence, multi-agent systems, collaborative and social computing, social networks, ubiquitous computing.

Evolutionary Computation

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Author : Kenneth A. De Jong
language : en
Publisher: MIT Press
Release Date : 2006-02-03

Evolutionary Computation written by Kenneth A. De Jong and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-03 with Computers categories.

This text is an introduction to the field of evolutionary computation. It approaches evolution strategies and genetic programming, as instances of a more general class of evolutionary algorithms.

Advances In Evolutionary Computing

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Author : Ashish Ghosh
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Advances In Evolutionary Computing written by Ashish Ghosh 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 2012-12-06 with Computers categories.

The term evolutionary computing refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution; thus the aim of designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution. These algo rithms are classified into three main categories, depending more on historical development than on major functional techniques. In fact, their biological basis is essentially the same. Hence EC = GA uGP u ES uEP EC = Evolutionary Computing GA = Genetic Algorithms,GP = Genetic Programming ES = Evolution Strategies,EP = Evolutionary Programming Although the details of biological evolution are not completely understood (even nowadays), there is some strong experimental evidence to support the following points: • Evolution is a process operating on chromosomes rather than on organ isms. • Natural selection is the mechanism that selects organisms which are well adapted to the environment toreproduce more often than those which are not. • The evolutionary process takes place during the reproduction stage that includes mutation (which causes the chromosomes of offspring to be dif ferent from those of the parents) and recombination (which combines the chromosomes of the parents to produce the offspring). Based upon these features, the previously mentioned three models of evolutionary computing were independently (and almost simultaneously) de veloped. An evolutionary algorithm (EA) is an iterative and stochastic process that operates on a set of individuals (called a population).