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Introduction to Genetic Algorithms, S.N. Sivanandam; S. N. Deepa


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Автор: S.N. Sivanandam; S. N. Deepa
Название:  Introduction to Genetic Algorithms
ISBN: 9783642092244
Издательство: Springer
Классификация:


ISBN-10: 3642092241
Обложка/Формат: Paperback
Страницы: 442
Вес: 0.64 кг.
Дата издания: 15.10.2010
Язык: English
Размер: 234 x 157 x 24
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems.


Introduction to Evolutionary Algorithms

Автор: Xinjie Yu; Mitsuo Gen
Название: Introduction to Evolutionary Algorithms
ISBN: 184996128X ISBN-13(EAN): 9781849961288
Издательство: Springer
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Цена: 27251.00 р.
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Описание: Introduction to Evolutionary Algorithms presents a comprehensive, up-to-date overview of evolutionary algorithms. Readers will find a discussion of hot topics in the field, including genetic algorithms, differential evolution, swarm intelligence, and artificial immune systems.

Genetic Algorithms for Applied CAD Problems

Автор: Viktor M. Kureichik; Sergey P. Malioukov; Vladimir
Название: Genetic Algorithms for Applied CAD Problems
ISBN: 3540852808 ISBN-13(EAN): 9783540852803
Издательство: Springer
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Цена: 20962.00 р.
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Описание: With new perspective technologies of genetic search and evolution simulation at the heart of this book, the authors wanted to show how these technologies are used for the solution of practical problems. This monograph is devoted to specialists of CAD.

An Introduction to Fuzzy Linear Programming Problems

Автор: Jagdeep Kaur; Amit Kumar
Название: An Introduction to Fuzzy Linear Programming Problems
ISBN: 3319312731 ISBN-13(EAN): 9783319312736
Издательство: Springer
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Цена: 15672.00 р.
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Описание: The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers.

Introduction to Annotated Logics

Автор: Jair Minoro Abe; Seiki Akama; Kazumi Nakamatsu
Название: Introduction to Annotated Logics
ISBN: 331917911X ISBN-13(EAN): 9783319179117
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book is written as an introduction to annotated logics. It provides logical foundations for annotated logics, discusses some interesting applications of these logics and also includes the authors` contributions to annotated logics.

Introduction to Evolutionary Algorithms

Автор: Xinjie Yu; Mitsuo Gen
Название: Introduction to Evolutionary Algorithms
ISBN: 144712569X ISBN-13(EAN): 9781447125693
Издательство: Springer
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Цена: 27251.00 р.
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Описание: Introduction to Evolutionary Algorithms presents a comprehensive, up-to-date overview of evolutionary algorithms. Readers will find a discussion of hot topics in the field, including genetic algorithms, differential evolution, swarm intelligence, and artificial immune systems.

Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

Автор: Muhammet ?nal; Ay?a Ak; Vedat Topuz; Hasan Erdal
Название: Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
ISBN: 3642434770 ISBN-13(EAN): 9783642434778
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book covers the theory behind artificial neural networks, genetic algorithms and the ant colony optimization algorithm, and presents a novel real time control algorithm using genetic and ant colony optimization algorithms for optimizing PID controllers.

Multiobjective Genetic Algorithms for Clustering

Автор: Ujjwal Maulik; Sanghamitra Bandyopadhyay; Anirban
Название: Multiobjective Genetic Algorithms for Clustering
ISBN: 3642439632 ISBN-13(EAN): 9783642439636
Издательство: Springer
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Цена: 7680.00 р.
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Описание: This book covers clustering using multiobjective genetic algorithms, with extensive real-life application in data mining and bioinformatics. The authors offer instructions for relevant techniques, and demonstrate real-world applications in several disciplines.

Representations for Genetic and Evolutionary Algorithms

Автор: D.E. Goldberg; Franz Rothlauf
Название: Representations for Genetic and Evolutionary Algorithms
ISBN: 3642880967 ISBN-13(EAN): 9783642880964
Издательство: Springer
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Цена: 6986.00 р.
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Описание: In the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given.

Genetic Algorithms: Principles and Perspectives

Автор: Colin R. Reeves; Jonathan E. Rowe
Название: Genetic Algorithms: Principles and Perspectives
ISBN: 147577818X ISBN-13(EAN): 9781475778182
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops.

Grouping Genetic Algorithms

Автор: Mutingi
Название: Grouping Genetic Algorithms
ISBN: 3319443933 ISBN-13(EAN): 9783319443935
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to specific variants of grouping genetic algorithms. Unique heuristic grouping techniques are developed to handle grouping problems efficiently and effectively. Illustrative examples and computational results are presented in tables and graphs to demonstrate the efficiency and effectiveness of the algorithms.Researchers, decision analysts, software developers, and graduate students from various disciplines will find this in-depth reader-friendly exposition of advances and applications of grouping genetic algorithms an interesting, informative and valuable resource.

Multi-Sensor Data Fusion: An Introduction

Автор: H.B. Mitchell
Название: Multi-Sensor Data Fusion: An Introduction
ISBN: 3642090672 ISBN-13(EAN): 9783642090677
Издательство: Springer
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Цена: 13059.00 р.
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Описание: This textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. No previous knowledge of multi-sensor data fusion is assumed, although some familiarity with the basic tools of linear algebra, calculus and simple probability theory is recommended.

Genetic Algorithms + Data Structures = Evolution Programs

Автор: Zbigniew Michalewicz
Название: Genetic Algorithms + Data Structures = Evolution Programs
ISBN: 3540606769 ISBN-13(EAN): 9783540606765
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control.


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