The Practical Handbook Of Genetic Algorithms
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The Practical Handbook Of Genetic Algorithms
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Author : Lance D. Chambers
language : en
Publisher: CRC Press
Release Date : 2000-12-07
The Practical Handbook Of Genetic Algorithms written by Lance D. Chambers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-12-07 with Computers categories.
Rapid developments in the field of genetic algorithms along with the popularity of the first edition precipitated this completely revised, thoroughly updated second edition of The Practical Handbook of Genetic Algorithms. Like its predecessor, this edition helps practitioners stay up to date on recent developments in the field and provides material
The Practical Handbook Of Genetic Algorithms
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Author : Lance D. Chambers
language : en
Publisher: CRC Press
Release Date : 2019-09-17
The Practical Handbook Of Genetic Algorithms written by Lance D. Chambers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-17 with Mathematics categories.
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
Practical Handbook Of Genetic Algorithms
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Author : Lance D. Chambers
language : en
Publisher: CRC Press
Release Date : 2019-09-17
Practical Handbook Of Genetic Algorithms written by Lance D. Chambers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-17 with Computers categories.
Practical Handbook of Genetic Algorithms, Volume 3: Complex Coding Systems contains computer-code examples for the development of genetic algorithm systems - compiling them from an array of practitioners in the field. Each contribution of this singular resource includes: unique code segments documentation descripti
Practical Genetic Algorithms
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Author : Randy L. Haupt
language : en
Publisher: John Wiley & Sons
Release Date : 2004-07-30
Practical Genetic Algorithms written by Randy L. Haupt and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-07-30 with Technology & Engineering categories.
* This book deals with the fundamentals of genetic algorithms and their applications in a variety of different areas of engineering and science * Most significant update to the second edition is the MATLAB codes that accompany the text * Provides a thorough discussion of hybrid genetic algorithms * Features more examples than first edition
The Practical Handbook Of Genetic Algorithms
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Author : Lance D. Chambers
language : en
Publisher: CRC Press
Release Date : 2019-09-17
The Practical Handbook Of Genetic Algorithms written by Lance D. Chambers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-17 with Mathematics categories.
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
Practical Handbook Of Genetic Algorithms
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Author : Taylor & Francis Group
language : en
Publisher: CRC Press
Release Date : 2020-09-30
Practical Handbook Of Genetic Algorithms written by Taylor & Francis Group and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-30 with categories.
Practical Handbook of Genetic Algorithms, Volume 3: Complex Coding Systems contains computer-code examples for the development of genetic algorithm systems - compiling them from an array of practitioners in the field. Each contribution of this singular resource includes: unique code segments documentation description of the operations performed rationale for the chosen approach problems the code overcomes or addresses Practical Handbook of Genetic Algorithms, Volume 3: Complex Coding Systems complements the first two volumes in the series by offering examples of computer code. The first two volumes dealt with new research and an overview of the types of applications that could be taken with GAs. This volume differs from its predecessors by specifically concentrating on specific functions in genetic algorithms, serving as the only compilation of useful and usable computer code in the field.
An Introduction To Genetic Algorithms
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Author : Melanie Mitchell
language : en
Publisher: MIT Press
Release Date : 1998-03-02
An Introduction To Genetic Algorithms written by Melanie Mitchell and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-03-02 with Computers categories.
Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
Genetic Algorithms And Genetic Programming
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Author : Michael Affenzeller
language : en
Publisher: CRC Press
Release Date : 2009-04-09
Genetic Algorithms And Genetic Programming written by Michael Affenzeller and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-09 with Computers categories.
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al
Genetic Algorithms In Java Basics
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Author : Lee Jacobson
language : en
Publisher: Apress
Release Date : 2015-11-28
Genetic Algorithms In Java Basics written by Lee Jacobson and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-28 with Computers categories.
Genetic Algorithms in Java Basics is a brief introduction to solving problems using genetic algorithms, with working projects and solutions written in the Java programming language. This brief book will guide you step-by-step through various implementations of genetic algorithms and some of their common applications, with the aim to give you a practical understanding allowing you to solve your own unique, individual problems. After reading this book you will be comfortable with the language specific issues and concepts involved with genetic algorithms and you'll have everything you need to start building your own. Genetic algorithms are frequently used to solve highly complex real world problems and with this book you too can harness their problem solving capabilities. Understanding how to utilize and implement genetic algorithms is an essential tool in any respected software developers toolkit. So step into this intriguing topic and learn how you too can improve your software with genetic algorithms, and see real Java code at work which you can develop further for your own projects and research. Guides you through the theory behind genetic algorithms Explains how genetic algorithms can be used for software developers trying to solve a range of problems Provides a step-by-step guide to implementing genetic algorithms in Java
Hands On Genetic Algorithms With Python
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Author : Eyal Wirsansky
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31
Hands On Genetic Algorithms With Python written by Eyal Wirsansky and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.
Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning models using Python libraries such as DEAP, scikit-learn, and NumPy Key Features Explore the ins and outs of genetic algorithms with this fast-paced guide Implement tasks such as feature selection, search optimization, and cluster analysis using Python Solve combinatorial problems, optimize functions, and enhance the performance of artificial intelligence applications Book DescriptionGenetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence. After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications. By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains.What you will learn Understand how to use state-of-the-art Python tools to create genetic algorithm-based applications Use genetic algorithms to optimize functions and solve planning and scheduling problems Enhance the performance of machine learning models and optimize deep learning network architecture Apply genetic algorithms to reinforcement learning tasks using OpenAI Gym Explore how images can be reconstructed using a set of semi-transparent shapes Discover other bio-inspired techniques, such as genetic programming and particle swarm optimization Who this book is for This book is for software developers, data scientists, and AI enthusiasts who want to use genetic algorithms to carry out intelligent tasks in their applications. Working knowledge of Python and basic knowledge of mathematics and computer science will help you get the most out of this book.