Optimization of Complex Systems: Theory, Models, Algorithms and Applications, Hoai An Le Thi; Hoai Minh Le; Tao Pham Dinh

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.

Автор: Kwok Tai Chui, Miltiadis D. Lytras, Ryan Wen Liu, Mingbo Zhao
Название: Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence
ISBN: 179983039X ISBN-13(EAN): 9781799830399
Издательство: Mare Nostrum (Eurospan)
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Цена: 291210.00 T
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Описание: While cognitive informatics and natural intelligence are receiving greater attention by researchers, multidisciplinary approaches still struggle with fundamental problems involving psychology and neurobiological processes of the brain. Examining the difficulties of certain approaches using the tools already available is vital for propelling knowledge forward and making further strides.

Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence is a collection of innovative research that examines the enhancement of human cognitive performance using emerging technologies. Featuring research on topics such as parallel computing, neuroscience, and signal processing, this book is ideally designed for engineers, computer scientists, programmers, academicians, researchers, and students.

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.

Автор: Oscar Castillo; Patricia Melin; Janusz Kacprzyk
Название: Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications
ISBN: 331989028X ISBN-13(EAN): 9783319890289
Издательство: Springer
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Цена: 186330.00 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.

Автор: Yujun Zheng; Xueqin Lu; Minxia Zhang; Shengyong Ch
Название: Biogeography-Based Optimization: Algorithms and Applications
ISBN: 9811325855 ISBN-13(EAN): 9789811325854
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors’ recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.

Автор: Yujun Zheng; Xueqin Lu; Minxia Zhang; Shengyong Ch
Название: Biogeography-Based Optimization: Algorithms and Applications
ISBN: 9811347948 ISBN-13(EAN): 9789811347948
Издательство: Springer
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Цена: 93160.00 T
Наличие на складе: Поставка под заказ.
Описание: This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors’ recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.

Автор: Houmin Yan; G. George Yin; Qing Zhang
Название: Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems
ISBN: 1441941487 ISBN-13(EAN): 9781441941480
Издательство: Springer
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Цена: 153720.00 T
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Описание: It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. The book is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday, in view of his distinguished career.

Автор: Kocay William
Название: Graphs, Algorithms, and Optimization
ISBN: 1482251167 ISBN-13(EAN): 9781482251166
Издательство: Taylor&Francis
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Цена: 83690.00 T
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Описание:

The second edition of this popular book presents the theory of graphs from an algorithmic viewpoint. The authors present the graph theory in a rigorous, but informal style and cover most of the main areas of graph theory. The ideas of surface topology are presented from an intuitive point of view. We have also included a discussion on linear programming that emphasizes problems in graph theory. The text is suitable for students in computer science or mathematics programs.

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.

Автор: Darko Vasiljevic
Название: Classical and Evolutionary Algorithms in the Optimization of Optical Systems
ISBN: 146135370X ISBN-13(EAN): 9781461353706
Издательство: Springer
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Цена: 46570.00 T
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Описание: The optimization of optical systems is a very old problem. For a long time the optimization of optical systems was connected with well-known mathematical theories of optimization which gave good results, but required lens designers to have a strong knowledge about optimized optical systems.

Автор: Chellappan
Название: Wireless Algorithms, Systems, and Applications
ISBN: 3319942670 ISBN-13(EAN): 9783319942674
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book constitutes the proceedings of the 13th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2018, held in Tianjin, China, in June 2018. The 59 full papers and 18 short papers presented in this book were carefully reviewed and selected from 197 submissions.

Автор: S. Rajasekaran, G.A. Vijayalakshmi Pai
Название: Neural Networks, Fuzzy Systems and Evolutionary Algorithms: Synthesis and Applications
ISBN: 812035334X ISBN-13(EAN): 9788120353343
Издательство: Mare Nostrum (Eurospan)
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Цена: 20330.00 T
Наличие на складе: Невозможна поставка.
Описание: Provides a comprehensive introduction to a consortium of technologies underlying soft computing. The constituent technologies discussed comprise neural network (NN), fuzzy system (FS), evolutionary algorithm (EA), and a number of hybrid systems, which include classes such as neuro-fuzzy, evolutionary-fuzzy, and neuro-evolutionary systems.