New Frontier In Evolutionary Algorithms: Theory And Applications
New Frontier In Evolutionary Algorithms: Theory And Applications

Author: Hitoshi Iba

Publisher: Imperial College Press

Published: 2011-08-26

Total Pages: 317

ISBN-13: 1911299557

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This book delivers theoretical and practical knowledge of Genetic Algorithms (GA) for the purpose of practical applications. It provides a methodology for a GA-based search strategy with the integration of several Artificial Life and Artificial Intelligence techniques, such as memetic concepts, swarm intelligence, and foraging strategies. The development of such tools contributes to better optimizing methodologies when addressing tasks from areas such as robotics, financial forecasting, and data mining in bioinformatics.The emphasis of this book is on applicability to the real world. Tasks from application areas - optimization of the trading rule in foreign exchange (FX) and stock prices, economic load dispatch in power system, exit/door placement for evacuation planning, and gene regulatory network inference in bioinformatics - are studied, and the resultant empirical investigations demonstrate how successful the proposed approaches are when solving real-world tasks of great importance.

Introduction to Evolutionary Computing
Introduction to Evolutionary Computing

Author: A.E. Eiben

Publisher: Springer Science & Business Media

Published: 2007-08-06

Total Pages: 328

ISBN-13: 9783540401841

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The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is 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. The 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 Algorithms and Chaotic Systems
Evolutionary Algorithms and Chaotic Systems

Author: Ivan Zelinka

Publisher: Springer Science & Business Media

Published: 2010-02-23

Total Pages: 533

ISBN-13: 3642107060

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This book discusses the mutual intersection of two fields of research: evolutionary computation, which can handle tasks such as control of various chaotic systems, and deterministic chaos, which is investigated as a behavioral part of evolutionary algorithms.

Illustrating Evolutionary Computation with Mathematica
Illustrating Evolutionary Computation with Mathematica

Author: Christian Jacob

Publisher: Elsevier

Published: 2001-02-23

Total Pages: 605

ISBN-13: 0080508456

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An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject.* Introduces the major mechanisms of biological evolution.* Demonstrates many fascinating aspects of evolution in nature with simple, yet illustrative examples.* Explains each of the major branches of evolutionary computation: genetic algorithms, genetic programming, evolutionary programming, and evolution strategies.* Demonstrates the programming of computers by evolutionary principles using Evolvica, a genetic programming system designed by the author.* Shows in detail how to evolve developmental programs modeled by cellular automata and Lindenmayer systems.* Provides Mathematica notebooks on the Web that include all the programs in the book and supporting animations, movies, and graphics.

Evolution in Computational Intelligence
Evolution in Computational Intelligence

Author: Vikrant Bhateja

Publisher: Springer Nature

Published: 2020-09-08

Total Pages: 780

ISBN-13: 9811557888

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This book presents the proceedings of 8th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2020), which aims to bring together researchers, scientists, engineers and practitioners to share new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. The book is divided into two volumes: Evolution in Computational Intelligence (Volume 1) and Intelligent Data Engineering and Analytics (Volume 2). Covering a broad range of topics in computational intelligence, the book features papers on theoretical as well as practical aspects of areas such as ANN and genetic algorithms, computer interaction, intelligent control optimization, evolutionary computing, intelligent e-learning systems, machine learning, mobile computing, and multi-agent systems. As such, it is a valuable reference resource for postgraduate students in various engineering disciplines.

Practical Applications of Evolutionary Computation to Financial Engineering
Practical Applications of Evolutionary Computation to Financial Engineering

Author: Hitoshi Iba

Publisher: Springer Science & Business Media

Published: 2012-02-15

Total Pages: 253

ISBN-13: 3642276482

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“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.

The Practical Handbook of Genetic Algorithms
The Practical Handbook of Genetic Algorithms

Author: Lance D. Chambers

Publisher: CRC Press

Published: 2019-09-17

Total Pages: 438

ISBN-13: 1420050079

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The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organism

Applications of Evolutionary Computing
Applications of Evolutionary Computing

Author: Mario Giacobini

Publisher: Springer Science & Business Media

Published: 2007-04-02

Total Pages: 775

ISBN-13: 3540718044

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This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2007, held in Valencia, Spain in April 2007. It examines evolutionary computation in communications, networks, and connected systems; finance and economics; image analysis and signal processing; and transportation and logistics. Coverage also details evolutionary algorithms in stochastic and dynamic environments.

Frontier Applications of Nature Inspired Computation
Frontier Applications of Nature Inspired Computation

Author: Mahdi Khosravy

Publisher: Springer Nature

Published: 2020-03-11

Total Pages: 402

ISBN-13: 9811521336

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This book addresses the frontier advances in the theory and application of nature-inspired optimization techniques, including solving the quadratic assignment problem, prediction in nature-inspired dynamic optimization, the lion algorithm and its applications, optimizing the operation scheduling of microgrids, PID controllers for two-legged robots, optimizing crane operating times, planning electrical energy distribution systems, automatic design and evaluation of classification pipelines, and optimizing wind-energy power generation plants. The book also presents a variety of nature-inspired methods and illustrates methods of adapting these to said applications. Nature-inspired computation, developed by mimicking natural phenomena, makes a significant contribution toward the solution of non-convex optimization problems that normal mathematical optimizers fail to solve. As such, a wide range of nature-inspired computing approaches has been used in multidisciplinary engineering applications. Written by researchers and developers from a variety of fields, this book presents the latest findings, novel techniques and pioneering applications.

Evolutionary Computation
Evolutionary Computation

Author: Wellington Santos

Publisher: BoD – Books on Demand

Published: 2009-10-01

Total Pages: 586

ISBN-13: 9533070080

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This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field.