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03795nam a22005415i 4500 |
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978-3-642-27479-4 |
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DE-He213 |
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20151125141027.0 |
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cr nn 008mamaa |
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120125s2012 gw | s |||| 0|eng d |
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|a 9783642274794
|9 978-3-642-27479-4
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|a 10.1007/978-3-642-27479-4
|2 doi
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|a Aguiar e Oliveira Junior, Hime.
|e author.
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|a Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing
|h [electronic resource] /
|c by Hime Aguiar e Oliveira Junior, Lester Ingber, Antonio Petraglia, Mariane Rembold Petraglia, Maria Augusta Soares Machado.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2012.
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|a XII, 207 p. 59 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
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|2 rdamedia
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|a online resource
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|a text file
|b PDF
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|a Intelligent Systems Reference Library,
|x 1868-4394 ;
|v 35
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|a Global optimization and its applications -- Heuristic methods -- Fuzzy adaptive simulated annealing -- Unconstrained optimization -- Constrained optimization -- Applications to signal processing -- Fuzzy modeling with fuzzy adaptive simulated annealing -- Statistical estimation and global optimization -- Nonlinear equation solving -- Space-filling curves and fuzzy ASA -- Epilogue.
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|a Stochastic global optimization is a very important subject, that has applications in virtually all areas of science and technology. Therefore there is nothing more opportune than writing a book about a successful and mature algorithm that turned out to be a good tool in solving difficult problems. Here we present some techniques for solving several problems by means of Fuzzy Adaptive Simulated Annealing (Fuzzy ASA), a fuzzy-controlled version of ASA, and by ASA itself. ASA is a sophisticated global optimization algorithm that is based upon ideas of the simulated annealing paradigm, coded in the C programming language and developed to statistically find the best global fit of a nonlinear constrained, non-convex cost function over a multi-dimensional space. By presenting detailed examples of its application we want to stimulate the reader’s intuition and make the use of Fuzzy ASA (or regular ASA) easier for everyone wishing to use these tools to solve problems. We kept formal mathematical requirements to a minimum and focused on continuous problems, although ASA is able to handle discrete optimization tasks as well. This book can be used by researchers and practitioners in engineering and industry, in courses on optimization for advanced undergraduate and graduate levels, and also for self-study.
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|a Engineering.
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|a Artificial intelligence.
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|a Applied mathematics.
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|a Engineering mathematics.
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|a Computational intelligence.
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|a Engineering.
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|a Computational Intelligence.
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|a Appl.Mathematics/Computational Methods of Engineering.
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|a Artificial Intelligence (incl. Robotics).
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| 700 |
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|a Ingber, Lester.
|e author.
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|a Petraglia, Antonio.
|e author.
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|a Rembold Petraglia, Mariane.
|e author.
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|a Augusta Soares Machado, Maria.
|e author.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9783642274787
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| 830 |
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|a Intelligent Systems Reference Library,
|x 1868-4394 ;
|v 35
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| 856 |
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|u http://dx.doi.org/10.1007/978-3-642-27479-4
|z Full Text via HEAL-Link
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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