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Nature-Inspired Algorithms and Applied Optimization, Xin-She Yang


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Цена: 139750.00T
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Склад Америка: 176 шт.  
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Ориентировочная дата поставки: Август-начало Сентября
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Автор: Xin-She Yang
Название:  Nature-Inspired Algorithms and Applied Optimization
ISBN: 9783319676685
Издательство: Springer
Классификация:



ISBN-10: 3319676687
Обложка/Формат: Hardcover
Страницы: 330
Вес: 0.66 кг.
Дата издания: 08.11.2017
Серия: Studies in Computational Intelligence
Язык: English
Размер: 234 x 156 x 21
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Mathematical Analysis of Nature-Inspired Algorithms.- A Review of No Free Lunch Theorems, and their Implications for Metaheuristic Optimisation.- Global Convergence Analysis of Cuckoo Search Using Markov Theory.- On Effeciently Solving the Vehicle Routing Problem with Time Windows Using the Bat Algorithm.- Variants of the Flower Pollination Algorithm: A Review.

A First Course in Optimization Theory

Автор: Sundaram, Rangarajan K.
Название: A First Course in Optimization Theory
ISBN: 0521497701 ISBN-13(EAN): 9780521497701
Издательство: Cambridge Academ
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Цена: 45410.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, first published in 1996, introduces students to optimization theory and its use in economics and allied disciplines.

Combinatorial Optimization (algorithms and Combinatorics 21) 5th ed.

Автор: Korte, Bernhard, Vygen, Jens
Название: Combinatorial Optimization (algorithms and Combinatorics 21) 5th ed.
ISBN: 3642244874 ISBN-13(EAN): 9783642244872
Издательство: Springer
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Цена: 60510.00 T
Наличие на складе: Невозможна поставка.
Описание: This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the fundamentals, covers the classical topics (paths, flows, matching, matroids, NP-completeness, approximation algorithms) in detail, and proceeds to advanced and recent topics, some of which have not appeared in a textbook before. Throughout, it contains complete but concise proofs, and also provides numerous exercises and references. This fifth edition has again been updated, revised, and significantly extended, with more than 60 new exercises and new material on various topics, including Cayley's formula, blocking flows, faster b-matching separation, multidimensional knapsack, multicommodity max-flow min-cut ratio, and sparsest cut. Thus, this book represents the state of the art of combinatorial optimization.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)

Автор: Natalio Krasnogor; Bel?n Meli?n-Batista; Jos? A. M
Название: Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)
ISBN: 3642260349 ISBN-13(EAN): 9783642260346
Издательство: Springer
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Цена: 204040.00 T
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Описание: As in these two previous editions, the aim of NICSO 2008, held in Tenerife, Spain, was to provide a forum where the latest ideas and state- of-the-art research related to nature inspired cooperative strategies for problem solving were discussed.

Advanced Optimization by Nature-Inspired Algorithms

Автор: Omid Bozorg-Haddad
Название: Advanced Optimization by Nature-Inspired Algorithms
ISBN: 9811052204 ISBN-13(EAN): 9789811052200
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Nature-Inspired Optimization Algorithms

Автор: Yang Xin She
Название: Nature-Inspired Optimization Algorithms
ISBN: 0128100605 ISBN-13(EAN): 9780128100608
Издательство: Elsevier Science
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Цена: 83080.00 T
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Описание: Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference.

Introduction to nature-inspired optimization

Автор: Lindfield, George (professor, School Of Engineering And Applied Science, Aston University) Penny, John (professor, School Of Engineering And Applied S
Название: Introduction to nature-inspired optimization
ISBN: 0128036362 ISBN-13(EAN): 9780128036365
Издательство: Elsevier Science
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Цена: 106620.00 T
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Описание:

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work.

Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization.


Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)

Автор: Natalio Krasnogor; Bel?n Meli?n-Batista; Jos? A. M
Название: Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)
ISBN: 3642032109 ISBN-13(EAN): 9783642032103
Издательство: Springer
Рейтинг:
Цена: 204040.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As in these two previous editions, the aim of NICSO 2008, held in Tenerife, Spain, was to provide a forum where the latest ideas and state- of-the-art research related to nature inspired cooperative strategies for problem solving were discussed.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Автор: Carlos Cruz; Juan R. Gonz?lez; Natalio Krasnogor;
Название: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)
ISBN: 3642125379 ISBN-13(EAN): 9783642125379
Издательство: Springer
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Цена: 204040.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as fresh algorithms based on the behaviour of fireflies or bats.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2011)

Автор: David Alejandro Pelta; Natalio Krasnogor; Dan Dumi
Название: Nature Inspired Cooperative Strategies for Optimization (NICSO 2011)
ISBN: 3642269915 ISBN-13(EAN): 9783642269912
Издательство: Springer
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Цена: 156720.00 T
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Описание: This book presents the latest ideas and techniques in nature inspired cooperative strategies, covering swarm intelligence; genetic algorithms; coevolution and cooperation; evolutionary design; hybrid algorithms and membrane computing (P-Systems) and more.

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Автор: Patricia Melin; Oscar Castillo; Janusz Kacprzyk
Название: Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization
ISBN: 331917746X ISBN-13(EAN): 9783319177465
Издательство: Springer
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Цена: 156720.00 T
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Описание: This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)

Автор: German Terrazas; Fernando E. B. Otero; Antonio D.
Название: Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)
ISBN: 3319033476 ISBN-13(EAN): 9783319033471
Издательство: Springer
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Цена: 121890.00 T
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Описание: Collecting research presented at NICSO 2013, this book reports on nature-inspired methods and applications including Swarm Intelligence, Hyper-heuristics, Evolutionary Algorithms, Cellular Automata, Artificial Bee Colony, Ant Clustering and many others.

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Автор: Patricia Melin; Oscar Castillo; Janusz Kacprzyk
Название: Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization
ISBN: 331936961X ISBN-13(EAN): 9783319369617
Издательство: Springer
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Цена: 139310.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems.


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