Last edited by Moogutaxe
Thursday, July 23, 2020 | History

3 edition of Computational intelligence in optimization found in the catalog.

Computational intelligence in optimization

applications and implementations

by Yoel Tenne

  • 332 Want to read
  • 2 Currently reading

Published by Springer in Berlin, Heidelberg .
Written in English

    Subjects:
  • Soft Computing,
  • Optimierungsproblem,
  • Mathematical optimization,
  • Computational intelligence

  • Edition Notes

    StatementYoel Tenne and Chi-Keong Goh (Eds.).
    SeriesAdaptation, learning, and optimization -- v. 7, Adaptation, learning, and optimization -- v. 7.
    Classifications
    LC ClassificationsQ342 .C6614 2010
    The Physical Object
    Paginationxx, 412 p. :
    Number of Pages412
    ID Numbers
    Open LibraryOL25313787M
    ISBN 103642127746
    ISBN 109783642127748
    LC Control Number2010926028
    OCLC/WorldCa643795552

    Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines. Talbe of Contents. 1. Introduction to Computational Intelligence Welcome to Computational Intelligence What Makes This Book. Xin-She Yang, in Nature-Inspired Optimization Algorithms, Applications. CS has been applied in many areas of optimization and computational intelligence with promising efficiency. For example, in engineering design applications, CS has superior performance over other algorithms for a range of continuous optimization problems, such as spring design and welded beam .

    Computational intelligence paradigms for optimization problems using MATLAB/SIMULINK | Kumar, L. Ashok; Sumathi, S.; Surekha, P | download | B–OK. Download books. Computational Intelligence describes a large, diverse, computation—along with their many variants, interact in meaningful ways to solve very complex problems. This book is an excellent introduc-tion to the field, greatly suited for an advanced undergraduate/beginning Particle Swarm Optimization 45 Toward Unification 47 Evolutionary File Size: KB.

    Computational Intelligence for Optimization is intended as a technical description of the state-of-the-art developments in advanced optimization techniques, specifically simulated annealing, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementation, and practical applications.   Computational intelligence (CI) encompasses a range of nature-inspired methods that exhibit intelligent behavior in complex clearly-structured, classroom-tested textbook/reference presents a methodical introduction to the field of CI. Providing an authoritative insight into all that is necessary for the successful application of CI methods, the book .


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Computational intelligence in optimization by Yoel Tenne Download PDF EPUB FB2

This book is not really an introduction to Computational Intelligence. For an introductory type of book read David E. Goldberg's Genetic Algorithms Book, it is exceptional in terms of readability, concepts presented and depths it gradually delves into.

That is the father of all genetic algorithm/EC/AI books, in my humble opinion/5(6). His book deserves a prominent space in every financial engineer's bookshelf." ―Gerald A.

Hanweck, Jr., PhD, CEO and Founder, Hanweck Associates, LLC "Applications of Computational Intelligence in Data-Driven Trading, is an essential addition to the library of any existing or endeavoring quantitative professional. This book is unique/5(9). Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/SIMULINK® - Ebook written by S.

Sumathi, L. Ashok Kumar, Surekha. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Computational Intelligence Paradigms for Optimization Problems.

This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings.

This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include:Brand: Springer-Verlag Berlin Heidelberg. Computational Intelligence for Optimization. Authors (view affiliations) Nirwan Ansari which have been proven to be effective in solving global optimization problems.

This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural. This volume presents some recent and principal developments related to computational intelligence and optimization methods in control.

Theoretical aspects and practical applications of control engineering are covered by 14 self-contained contributions. Computational Intelligence Paradigms for Optimization Problems Using MATLAB ® / Simulink ® explores the performance of CI in terms of knowledge representation, adaptability, optimality, and processing speed for different real-world optimization problems.

Focusing on the practical implementation of CI techniques, this book. This book lays emphasis on practical applications and computational tools, which are very useful and important for further development of the computational intelligence field.

Focusing on evolutionary computation, neural networks, and fuzzy logic, the authors have constructed an approach to thinking about and working with computational. "Computational Intelligence in Optimization" is a comprehensive reference for researchers, practitioners and advanced-level students interested in both the theory and practice of using computational intelligence in real-world applications.

Book Description. Considered one of the most innovative research directions, computational intelligence (CI) embraces techniques that use global search optimization, machine learning, approximate reasoning, and connectionist systems to develop efficient, robust, and easy-to-use solutions amidst multiple decision variables, complex constraints, and tumultuous environments.

From its institution as the Neural Networks Council in the early s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms.

The Society offers leading research in nature-inspired problem solving, including neural networks, evolutionary. This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation.

The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to. About the Book.

In the aerospace sciences, computational intelligence techniques are now key tools in addressing many problems. Such techniques have progressed along with increases in computing power, allowing numerical simulation to gradually replace experimental testing in many areas of engineering, and leading to an increasing use of nature-inspired numerical.

Computational Intelligence: Considers real world problems in the domain of systems modelling, control and optimization; He has published over scientific research papers in journals and conferences including seven book chapters and two books.

He is a senior member of the IEEE and has been involved in organising many international. Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments.

The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, 5/5(1). Additional Physical Format: Online version: Ansari, Nirwan, Computational intelligence for optimization.

Boston: Kluwer Academic, © (OCoLC) Computational Intelligence An Introduction Second Edition Andries P. Engelbrecht University of Pretoria names and product names used in this book are trade names, service marks, trademarks or registered Part IV COMPUTATIONAL SWARM INTELLIGENCE 16 Particle Swarm Optimization   Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems.

This book provides scholars, academics, and practitioners with a fundamental, comprehensive. "Computational Intelligence in Optimization" is a comprehensive reference for researchers, practitioners and advanced-level students interested in both the theory and practice of using computational intelligence in real-world applications.

show more. Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments.

The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral.

Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques focuses on methods to estimate missing values given to observed data. Providing a defining body of research valuable to those involved in the field of study, this book presents current and new computational intelligence.This book will appeal to professional and academic researchers in computational intelligence applications, tool development, and systems.

Key Features Moves clearly and efficiently from concepts and paradigms to algorithms and implementation techniques by focusing, in the early chapters, on the specific concepts and paradigms that inform the.This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems.

Topics covered include: • Dedicated implementations of evolutionary.