Описание: The book presents recently developed efficient metaheuristic optimization algorithms and their applications for solving various optimization problems in civil engineering. The concepts can also be used for optimizing problems in mechanical and electrical engineering.
Автор: Patrick Siarry Название: Metaheuristics ISBN: 3319454013 ISBN-13(EAN): 9783319454016 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Simulated Annealing.- Tabu Search.- Search in Variable Neighborhoods.- The GRASP Search Algorithm.- Evolutionary Algorithms.- Artificial Ants.- Particle Swarms.- Other Metaheuristics.- Other Social Insect Algorithms.- Extending Evolutionary Algorithms for Multiobjective Optimization.- Extending Evolutionary Algorithms for Optimization Under Constraints.- Modeling and Comparison Methods.- Hybrid Metaheuristics for Optimizing Logistics.- Metaheuristics for Vehicle Routing Problems.- Applications in Air Traffic Management.
Автор: Mauro Birattari Название: Tuning Metaheuristics ISBN: 3642101496 ISBN-13(EAN): 9783642101496 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Metaheuristics are a relatively new but already established approachto c- binatorial optimization. A metaheuristic is a generic algorithmic template that can be used for ?nding high quality solutions of hard combinatorial - timization problems. To arrive at a functioning algorithm, a metaheuristic needs to be con?gured: typically some modules need to be instantiated and someparametersneedto betuned.Icallthese twoproblems"structural"and "parametric" tuning, respectively. More generally, I refer to the combination of the two problems as "tuning." Tuning is crucial to metaheuristic optimization both in academic research andforpracticalapplications.Nevertheless, relativelylittle researchhasbeen devoted to the issue. This book shows that the problem of tuning a me- heuristic can be described and solved as a machine learning problem. Using the machine learning perspective, it is possible to give a formal de?nitionofthetuningproblemandtodevelopagenericalgorithmfortuning metaheuristics.Moreover, fromthemachinelearningperspectiveitispossible tohighlightsome?awsinthecurrentresearchmethodologyandtostatesome guidelines for future empirical analysis in metaheuristics research. This book is based on my doctoral dissertation and contains results I have obtained starting from 2001 while working within the Metaheuristics Net- 1 work. During these years I have been a?liated with two research groups: INTELLEKTIK, Technische Universit t Darmstadt, Darmstadt, Germany and IRIDIA, Universit Libre de Bruxelles, Brussels, Belgium. I am the- fore grateful to the research directors of these two groups: Prof. Wolfgang Bibel, Dr. Thomas St tzle, Prof. Philippe Smets, Prof. Hugues Bersini, and Prof. Marco Dorigo.
Автор: Lazzerini Название: Fuzzy Sets & their Application to Clustering & Training ISBN: 0849305896 ISBN-13(EAN): 9780849305894 Издательство: Taylor&Francis Рейтинг: Цена: 26796.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Fuzzy logic applications allow uncertain or imprecise data to be clustered and analyzed when traditional methods cannot be used. This volume offers an introduction to fuzzy set theory and then progresses through the algorithms and techniques used to manipulate data using fuzzy sets, including classification, hierarchy, and cluster structure.
Автор: Felipe M. G. Fran?a; Alberto Ferreira de Souza Название: Intelligent Text Categorization and Clustering ISBN: 3540856439 ISBN-13(EAN): 9783540856436 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Researchers have employed many intelligent techniques for text categorization and clustering, ranging from support vector machines and neural networks to Bayesian inference and algebraic methods, such as Latent Semantic Indexing. This volume offers a wide spectrum of research work developed for intelligent text categorization and clustering.
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