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Titlebook: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV; International Confer Michael Emmerich,Andre

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發(fā)表于 2025-3-21 19:55:59 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV
副標題International Confer
編輯Michael Emmerich,Andre Deutz,Carlos A. Coello
視頻videohttp://file.papertrans.cn/301/300631/300631.mp4
概述Latest research on Probability, Set Oriented Numerics, and Evolutionary Computation.Results of EVOLVE 2013 conference held July 11-13 2013 at Leiden, the Netherlands.Written by experts in the field
叢書名稱Advances in Intelligent Systems and Computing
圖書封面Titlebook: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV; International Confer Michael Emmerich,Andre
描述.Numerical and computational methods are nowadays used in a wide range of contexts in complex systems research, biology, physics, and engineering.? Over the last decades different methodological schools have emerged with emphasis on different aspects of computation, such as nature-inspired algorithms, set oriented numerics, probabilistic systems and Monte Carlo methods. Due to the use of different terminologies and emphasis on different aspects of algorithmic performance there is a strong need for a more integrated view and opportunities for cross-fertilization across particular disciplines. .These proceedings feature 20 original publications from distinguished authors in the cross-section of computational sciences, such as machine learning algorithms and probabilistic models, complex networks and fitness landscape analysis, set oriented numerics and cell mapping, evolutionary multiobjective optimization, diversity-oriented search, and the foundations of genetic programming algorithms. By presenting cutting edge results with a strong focus on foundations and integration aspects this work presents a stepping stone towards efficient, reliable, and well-analyzed methods for complex sy
出版日期Conference proceedings 2013
關鍵詞EVOLVE 2013; Evolutionary Computation; Intelligent Computing; Probability; Set Oriented Numerics
版次1
doihttps://doi.org/10.1007/978-3-319-01128-8
isbn_softcover978-3-319-01127-1
isbn_ebook978-3-319-01128-8Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer International Publishing Switzerland 2013
The information of publication is updating

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Unsupervised Classifier Based on Heuristic Optimization and Maximum Entropy Principle,are interesting properties. This implies a singular process of classification usually denoted as "clustering", where the objects are grouped into . subsets (clusters) in accordance with an appropriate measure of likelihood. Clustering can be considered the most important unsupervised learning proble
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Sewer Network Design Optimization Problem Using Ant Colony Optimization Algorithm and Tree Growing . ACOA has a unique feature namely incremental solution building mechanism which is used here for this problem. Layout and pipe size optimization of sewer network is a highly constrained Mixed-Integer Nonlinear Programming (MINLP) problem presenting a challenge even to the modern heuristic search me
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A Benchmark on the Interaction of Basic Variation Operators in Multi-objective Peptide Design Evalu general for several well-known reasons. Multi-objective evolutionary algorithms (MOEAs) introduce adequate in silico methods for finding optimal peptide sequences which optimize several molecular properties. A mutation-specific fast non-dominated sorting GA (termed MSNSGA-II) is especially designed
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