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Brain Storm Optimization Algorithms, Shi Cheng; Yuhui Shi


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Цена: 139750.00T
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Склад Америка: 255 шт.  
При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Shi Cheng; Yuhui Shi
Название:  Brain Storm Optimization Algorithms
ISBN: 9783030150693
Издательство: Springer
Классификация:

ISBN-10: 3030150690
Обложка/Формат: Hardcover
Страницы: 299
Вес: 0.64 кг.
Дата издания: 2019
Серия: Adaptation, Learning, and Optimization
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 100 tables, color; 58 illustrations, color; 50 illustrations, black and white; xv, 299 p. 108 illus., 58 illus. in color.
Размер: 234 x 156 x 19
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Подзаголовок: Concepts, Principles and Applications
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:
Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence.
This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.

Дополнительное описание: Brain Storm Optimization Algorithms: More Questions than Answers.- Brain Storm Optimization for Test Task Scheduling Problem.- Oppositional Brain Storm Optimization for Fault Section Location in Distribution Networks.- Multi-objective Brain Storm Optimiza


Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Автор: M.C. Bhuvaneswari
Название: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
ISBN: 8132219570 ISBN-13(EAN): 9788132219576
Издательство: Springer
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Цена: 130430.00 T
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Описание: This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.

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 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: 139750.00 T
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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.

Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

Автор: Oscar Castillo; Patricia Melin; Janusz Kacprzyk
Название: Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications
ISBN: 3319710079 ISBN-13(EAN): 9783319710075
Издательство: Springer
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Цена: 204970.00 T
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Описание: This book comprises papers on diverse aspects of fuzzy logic, neural networks, and nature-inspired optimization meta-heuristics and their application in various areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book is organized into seven main parts, each with a collection of papers on a similar subject. The first part presents new concepts and algorithms based on type-2 fuzzy logic for dynamic parameter adaptation in meta-heuristics. The second part discusses network theory and applications, and includes papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The third part addresses the theory and practice of meta-heuristics in different areas of application, while the fourth part describes diverse fuzzy logic applications in the control area, which can be considered as intelligent controllers. The next two parts explore applications in areas, such as time series prediction, and pattern recognition and new optimization and evolutionary algorithms and their applications respectively. Lastly, the seventh part addresses the design and application of different hybrid intelligent systems.

Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic

Автор: Frumen Olivas; Fevrier Valdez; Oscar Castillo; Pat
Название: Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic
ISBN: 3319708503 ISBN-13(EAN): 9783319708508
Издательство: Springer
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Цена: 51230.00 T
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Описание: Introduction.- Theory and Background.- Problems Statement.- Methodology.- Simulation Results.- Statistical Analysis and Comparison of Results.

Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

Автор: Muhammet ?nal; Ay?a Ak; Vedat Topuz; Hasan Erdal
Название: Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
ISBN: 3642434770 ISBN-13(EAN): 9783642434778
Издательство: Springer
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Цена: 104480.00 T
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Описание: This book covers the theory behind artificial neural networks, genetic algorithms and the ant colony optimization algorithm, and presents a novel real time control algorithm using genetic and ant colony optimization algorithms for optimizing PID controllers.

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Автор: M.C. Bhuvaneswari
Название: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems
ISBN: 8132235398 ISBN-13(EAN): 9788132235392
Издательство: Springer
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Цена: 95770.00 T
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Описание: This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.

Motion Planning in Medicine: Optimization and Simulation Algorithms for Image-Guided Procedures

Автор: Ron Alterovitz; Ken Goldberg
Название: Motion Planning in Medicine: Optimization and Simulation Algorithms for Image-Guided Procedures
ISBN: 3642088740 ISBN-13(EAN): 9783642088742
Издательство: Springer
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Цена: 111790.00 T
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Описание: Written by Ron Alterovitz and Ken Goldberg, this monograph combines ideas from robotics, physically-based modeling, and operations research to develop new motion planning and optimization algorithms for image-guided medical procedures.

Computational Optimization, Methods and Algorithms

Автор: Slawomir Koziel; Xin-She Yang
Название: Computational Optimization, Methods and Algorithms
ISBN: 3662520044 ISBN-13(EAN): 9783662520048
Издательство: Springer
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Цена: 130590.00 T
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Описание: Computational optimization is an important paradigm with a wide range of applications. This book reviews and discusses the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization.

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: 46570.00 T
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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.

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance

Автор: Pandian Vasant
Название: Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance
ISBN: 1466620862 ISBN-13(EAN): 9781466620865
Издательство: Mare Nostrum (Eurospan)
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Цена: 189420.00 T
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Описание: Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance, and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

Emerging Research On Swarm Intelligence And Algorithm Optimization

Автор: Shi
Название: Emerging Research On Swarm Intelligence And Algorithm Optimization
ISBN: 1466663286 ISBN-13(EAN): 9781466663282
Издательство: Mare Nostrum (Eurospan)
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Цена: 218990.00 T
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Описание: Throughout time, scientists have looked to nature in order to understand and model solutions for complex real-world problems. In particular, the study of self-organizing entities, such as social insect populations, presents a new opportunity within the field of artificial intelligence.>Emerging Research on Swarm Intelligence and Algorithm Optimization discusses current research analyzing how the collective behavior of decentralized systems in the natural world can be applied to intelligent system design. Discussing the application of swarm principles, optimization techniques, and key algorithms being used in the field, this publication serves as an essential reference for academicians, upper-level students, IT developers, and IT theorists.


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