Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction, Soto Jesus, Melin Patricia, Castillo Oscar

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
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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.

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.

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: Song Tao, Zheng Pan, Wong Dennis Mou Ling, Wang Xu
Название: Bio-inspired Computing Models And Algorithms
ISBN: 9813143177 ISBN-13(EAN): 9789813143173
Издательство: World Scientific Publishing
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Цена: 126720.00 T
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Описание:

Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics.

The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems.

Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well.

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
Наличие на складе: Есть у поставщика Поставка под заказ.
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: 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.

Автор: Monidipa Das; Soumya K. Ghosh
Название: Enhanced Bayesian Network Models for Spatial Time Series Prediction
ISBN: 3030277488 ISBN-13(EAN): 9783030277482
Издательство: Springer
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Цена: 139750.00 T
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Описание: This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The monograph is primarily prepared for graduate students of Computer Science, who wish to employ probabilistic graphical models, especially Bayesian networks (BNs), for applied research on spatial/spatio-temporal data.