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Advanced Optimization by Nature-Inspired Algorithms, Omid Bozorg-Haddad


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Цена: 12577.00р.
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Автор: Omid Bozorg-Haddad
Название:  Advanced Optimization by Nature-Inspired Algorithms
ISBN: 9789811353451
Издательство: Springer
Классификация:





ISBN-10: 981135345X
Обложка/Формат: Soft cover
Страницы: 159
Вес: 0.28 кг.
Дата издания: 2018
Серия: Studies in Computational Intelligence
Язык: English
Издание: Softcover reprint of
Иллюстрации: 4 illustrations, color; 30 illustrations, black and white; xv, 159 p. 34 illus., 4 illus. in color.
Размер: 234 x 156 x 10
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
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.
Дополнительное описание: Introduction.- Cat Swarm Optimization (CSO) Algorithm.- League Championship Algorithm (LCA).- Anarchic Society Optimization (ASO) Algorithm.- Cuckoo Optimization Algorithm (COA).- Teaching-Learning-Based Optimization (TLBO) Algorithm.- Flower pollination



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
Рейтинг:
Цена: 18167.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.

Modern Music-Inspired Optimization Algorithms for Electric Power Systems

Автор: Mohammad Kiani-Moghaddam; Mojtaba Shivaie; Philip
Название: Modern Music-Inspired Optimization Algorithms for Electric Power Systems
ISBN: 3030120430 ISBN-13(EAN): 9783030120436
Издательство: Springer
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Цена: 27950.00 р.
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Описание:

In today’s world, with an increase in the breadth and scope of real-world engineering optimization problems as well as with the advent of big data, improving the performance and efficiency of algorithms for solving such problems has become an indispensable need for specialists and researchers. In contrast to conventional books in the field that employ traditional single-stage computational, single-dimensional, and single-homogeneous optimization algorithms, this book addresses multiple newfound architectures for meta-heuristic music-inspired optimization algorithms. These proposed algorithms, with multi-stage computational, multi-dimensional, and multi-inhomogeneous structures, bring about a new direction in the architecture of meta-heuristic algorithms for solving complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data. The architectures of these new algorithms may also be appropriate for finding an optimal solution or a Pareto-optimal solution set with higher accuracy and speed in comparison to other optimization algorithms, when feasible regions of the solution space and/or dimensions of the optimization problem increase.
This book, unlike conventional books on power systems problems that only consider simple and impractical models, deals with complicated, techno-economic, real-world, large-scale models of power systems operation and planning. Innovative applicable ideas in these models make this book a precious resource for specialists and researchers with a background in power systems operation and planning.
Provides an understanding of the optimization problems and algorithms, particularly meta-heuristic optimization algorithms, found in fields such as engineering, economics, management, and operations research;Enhances existing architectures and develops innovative architectures for meta-heuristic music-inspired optimization algorithms in order to deal with complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data;Addresses innovative multi-level, techno-economic, real-world, large-scale, computational-logical frameworks for power systems operation and planning, and illustrates practical training on implementation of the frameworks using the meta-heuristic music-inspired optimization algorithms.
Handbook of research on soft computing and nature-inspired algorithms

Автор: SHANDILYA, SHANDILYA, DEEP & NAG
Название: Handbook of research on soft computing and nature-inspired algorithms
ISBN: 1522521283 ISBN-13(EAN): 9781522521280
Издательство: Turpin
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Цена: 41395.00 р.
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Описание: Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)

Автор: Natalio Krasnogor; Vincenzo Nicosia; Mario Pavone;
Название: Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)
ISBN: 3642097790 ISBN-13(EAN): 9783642097799
Издательство: Springer
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Цена: 27950.00 р.
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Описание: The aim of NICSO 2007 was to provide a forum where the latest ideas and state-of-the-art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected here were strictly peer reviewed.

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: 23508.00 р.
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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.

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: 12462.00 р.
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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.

Nature-Inspired Algorithms and Applied Optimization

Автор: Xin-She Yang
Название: Nature-Inspired Algorithms and Applied Optimization
ISBN: 3319676687 ISBN-13(EAN): 9783319676685
Издательство: Springer
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Цена: 20962.00 р.
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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.

Nature-Inspired Algorithms and Applied Optimization

Автор: Xin-She Yang
Название: Nature-Inspired Algorithms and Applied Optimization
ISBN: 3319884654 ISBN-13(EAN): 9783319884653
Издательство: Springer
Рейтинг:
Цена: 20962.00 р.
Наличие на складе: Поставка под заказ.

Описание: This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction

Автор: Soto Jesus, Melin Patricia, Castillo Oscar
Название: Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction
ISBN: 3319712632 ISBN-13(EAN): 9783319712635
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book focuses on the fields of hybrid intelligent systems based on fuzzy systems, neural networks, bio-inspired algorithms and time series. Prediction errors are evaluated by the following metrics: Mean Absolute Error, Mean Square Error, Root Mean Square Error, Mean Percentage Error and Mean Absolute Percentage Error.

Optimization using evolutionary algorithms and metaheuristics

Автор: Kaushik Kumar and J. Paulo Davim
Название: Optimization using evolutionary algorithms and metaheuristics
ISBN: 0367260441 ISBN-13(EAN): 9780367260446
Издательство: Taylor&Francis
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Цена: 25265.00 р.
Наличие на складе: Поставка под заказ.

Описание: This book covers developments and advances of algorithm based optimization techniques These techniques were only used for non-engineering problems. This book applies them to engineering problems.

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
Рейтинг:
Цена: 30606.00 р.
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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.

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: 30606.00 р.
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.


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