Practical Genetic Algorithms
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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
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
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 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
Parallel Genetic Algorithms
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Author : Gabriel Luque
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-15
Parallel Genetic Algorithms written by Gabriel Luque 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 2011-06-15 with Computers categories.
This book is the result of several years of research trying to better characterize parallel genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers can learn how to solve complex tasks by reducing their high computational times. Dealing with two scientific fields (parallelism and GAs) is always difficult, and the book seeks at gracefully introducing from basic concepts to advanced topics. The presentation is structured in three parts. The first one is targeted to the algorithms themselves, discussing their components, the physical parallelism, and best practices in using and evaluating them. A second part deals with the theory for pGAs, with an eye on theory-to-practice issues. A final third part offers a very wide study of pGAs as practical problem solvers, addressing domains such as natural language processing, circuits design, scheduling, and genomics. This volume will be helpful both for researchers and practitioners. The first part shows pGAs to either beginners and mature researchers looking for a unified view of the two fields: GAs and parallelism. The second part partially solves (and also opens) new investigation lines in theory of pGAs. The third part can be accessed independently for readers interested in applications. The result is an excellent source of information on the state of the art and future developments in parallel GAs.
An Introduction To Genetic Algorithms For Scientists And Engineers
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Author : David A. Coley
language : en
Publisher: World Scientific
Release Date : 1999
An Introduction To Genetic Algorithms For Scientists And Engineers written by David A. Coley and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematics categories.
This invaluable book has been designed to be useful to most practising scientists and engineers, whatever their field and however rusty their mathematics and programming might be. The approach taken is largely practical, with algorithms being presented in full and working code (in BASIC, FORTRAN, PASCAL AND C) included on a floppy disk to help the reader get up and running as quickly as possible. The text could also be used as part of an undergraduate course on search and optimisation. Student exercises are included at the end of several of the chapters, many of which are computer-based and designed to encourage exploration of the method.
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.
Artificial Intelligence Methods In The Environmental Sciences
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Author : Sue Ellen Haupt
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-11-28
Artificial Intelligence Methods In The Environmental Sciences written by Sue Ellen Haupt 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 2008-11-28 with Science categories.
How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Introduction To Genetic Algorithms
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Author : S.N. Sivanandam
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-24
Introduction To Genetic Algorithms written by S.N. Sivanandam 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 2007-10-24 with Technology & Engineering categories.
Theoriginofevolutionaryalgorithmswasanattempttomimicsomeoftheprocesses taking place in natural evolution. Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence: • Evolution is a process operating over chromosomes rather than over organisms. The former are organic tools encoding the structure of a living being, i.e., a cr- ture is “built” decoding a set of chromosomes. • Natural selection is the mechanism that relates chromosomes with the ef ciency of the entity they represent, thus allowing that ef cient organism which is we- adapted to the environment to reproduce more often than those which are not. • The evolutionary process takes place during the reproduction stage. There exists a large number of reproductive mechanisms in Nature. Most common ones are mutation (that causes the chromosomes of offspring to be different to those of the parents) and recombination (that combines the chromosomes of the parents to produce the offspring). Based upon the features above, the three mentioned models of evolutionary c- puting were independently (and almost simultaneously) developed.
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