Artificial Neural Networks And Type 2 Fuzzy Set
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Artificial Neural Networks And Type 2 Fuzzy Set
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Author : Snehashish Chakraverty
language : en
Publisher: Elsevier
Release Date : 2025-03-06
Artificial Neural Networks And Type 2 Fuzzy Set written by Snehashish Chakraverty and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-06 with Computers categories.
Soft computing is an emerging discipline which aims to exploit tolerance for imprecision, approximate reasoning, and uncertainty to achieve robustness, tractability, and cost effectiveness for building intelligent machines. Soft computing methodologies include neural networks, fuzzy sets, genetic algorithms, Bayesian networks, and rough sets, among others. In this regard, neural networks are widely used for modeling dynamic solvers, classification of data, and prediction of solutions, whereas fuzzy sets provide a natural framework for dealing with uncertainty. Artificial Neural Networks and Type-2 Fuzzy Set: Elements of Soft Computing and Its Applications covers the fundamental concepts and the latest research on variants of Artificial Neural Networks (ANN), including scientific machine learning and Type-2 Fuzzy Set (T2FS). In addition, the book also covers different applications for solving real-world problems along with various examples and case studies. It may be noted that quite a bit of research has been done on ANN and Fuzzy Set theory/ Fuzzy logic. However, Artificial Neural Networks and Type-2 Fuzzy Set is the first book to cover the use of ANN and fuzzy set theory with regards to Type-2 Fuzzy Set in static and dynamic problems in one place. Artificial Neural Networks and Type-2 Fuzzy Sets are two of the most widely used computational intelligence techniques for solving complex problems in various domains. Both ANN and T2FS have unique characteristics that make them suitable for different types of problems. This book provides the reader with in-depth understanding of how to apply these computational intelligence techniques in various fields of science and engineering in general and static and dynamic problems in particular. Further, for validation purposes of the ANN and fuzzy models, the obtained solutions of each model in the book is compared with already existing solutions that have been obtained with numerical or analytical methods. - Covers the fundamental concepts and the latest research on variants of Artificial Neural Networks, including scientific machine learning and Type-2 Fuzzy Set - Discusses the integration of ANN and Type-2 Fuzzy Set, showing how combining these two approaches can enhance the performance and robustness of intelligent systems - Demonstrates how to solve scientific and engineering research problems through a variety of real-world examples and case studies - Includes coverage of both static and dynamic problems, along with validation of ANN and Fuzzy models by comparing the obtained solutions of each model with already existing solutions that have been obtained with numerical or analytical methods
Type 2 Fuzzy Logic Theory And Applications
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Author : Oscar Castillo
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-20
Type 2 Fuzzy Logic Theory And Applications written by Oscar Castillo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-20 with Mathematics categories.
This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing (SC) techniques. The authors extend the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. This book is intended to be a major reference tool and can be used as a textbook.
Type 2 Fuzzy Neural Networks And Their Applications
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Author : Rafik Aziz Aliev
language : en
Publisher: Springer
Release Date : 2014-09-08
Type 2 Fuzzy Neural Networks And Their Applications written by Rafik Aziz Aliev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-08 with Computers categories.
This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination with other paradigms of Soft Computing technology such as Neuro-Computing and Evolutionary Computing. It provides a self-contained exposition of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students of universities and colleges, for scientists and practitioners from various fields such as control, decision analysis, pattern recognition and similar fields.
Advances In Type 2 Fuzzy Sets And Systems
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Author : Alireza Sadeghian
language : en
Publisher: Springer
Release Date : 2013-06-25
Advances In Type 2 Fuzzy Sets And Systems written by Alireza Sadeghian and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-25 with Technology & Engineering categories.
This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet. The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.
Type 2 Fuzzy Logic In Control Of Nonsmooth Systems
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Author : Oscar Castillo
language : en
Publisher: Springer
Release Date : 2018-11-02
Type 2 Fuzzy Logic In Control Of Nonsmooth Systems written by Oscar Castillo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-02 with Technology & Engineering categories.
This book presents the synthesis and analysis of fuzzy controllers and its application to a class of mechanical systems. It mainly focuses on the use of type-2 fuzzy controllers to account for disturbances known as hard or nonsmooth nonlinearities. The book, which summarizes the authors’ research on type-2 fuzzy logic and control of mechanical systems, presents models, simulation and experiments towards the control of servomotors with dead-zone and Coulomb friction, and the control of both wheeled mobile robots and a biped robot. Closed-loop systems are analyzed in the framework of smooth and nonsmooth Lyapunov functions.
Type 2 Fuzzy Logic In Intelligent Control Applications
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Author : Oscar Castillo
language : en
Publisher: Springer
Release Date : 2011-11-08
Type 2 Fuzzy Logic In Intelligent Control Applications written by Oscar Castillo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-08 with Computers categories.
We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts, which contain a group of chapters around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which can be the basis for achieving intelligent control with interval type-2 fuzzy logic. The second part of the book is comprised of chapters with the main theme of evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamics systems and hardware implementations. The third part of the book is formed with chapters dealing with the theme of bio-inspired optimization of type-2 fuzzy systems in intelligent control, which includes the application of particle swarm intelligence and ant colony optimization algorithms for obtaining optimal type-2 fuzzy controllers.
Hybrid Competitive Learning Method Using The Fireworks Algorithm And Artificial Neural Networks
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Author : Fevrier Valdez
language : en
Publisher: Springer Nature
Release Date : 2023-11-25
Hybrid Competitive Learning Method Using The Fireworks Algorithm And Artificial Neural Networks written by Fevrier Valdez and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Computers categories.
This book focuses on the fields of neural networks, swarm optimization algorithms, clustering and fuzzy logic. This book describes a hybrid method with three different techniques of intelligence computation: neural networks, optimization algorithms and fuzzy logic. Within the neural network techniques, competitive neural networks (CNNs) are used, for the optimization algorithms technique, we used the fireworks algorithm (FWA), and in the area of fuzzy logic, the Type-1 Fuzzy Inference Systems (T1FIS) and the Interval Type-2 Fuzzy Inference Systems (IT2FIS) were used, with their variants of Mamdani and Sugeno type, respectively. FWA was adapted for data clustering with the goal to help of competitive neural network to find the optimal number of neurons. It is important to mention that two variants were applied to the FWA: dynamically adjust of parameters with Type-1 Fuzzy Logic (FFWA) as the first one and Interval Type-2 (F2FWA) as the second one. Subsequently, based on the outputs of the CNN and with the goal of classification data, we designed Type-1 and Interval Type-2 Fuzzy Inference Systems of Mamdani and Sugeno type. This book is intended to be a reference for scientists and engineers interested in applying a different metaheuristic or an artificial neural network in order to solve optimization and applied fuzzy logic techniques for solving problems in clustering and classification data. This book is also used as a reference for graduate courses like the following: soft computing, swarm optimization algorithms, clustering data, fuzzy classify and similar ones. We consider that this book can also be used to get novel ideas for new lines of research, new techniques of optimization or to continue the lines of the research proposed by the authors of the book.
Interval Type 2 Fuzzy Sets And Interval Neutrosophic Sets In Intelligent Systems
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Author : M. LATHA MAHESWARI M.
language : en
Publisher: Infinite Study
Release Date :
Interval Type 2 Fuzzy Sets And Interval Neutrosophic Sets In Intelligent Systems written by M. LATHA MAHESWARI M. and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
In this thesis, interval type-2 fuzzy sets (IT2FSs) and interval neutrosophic sets (INSs) have been considered for all the proposed concepts. Fusion of information is an essential task to get the optimized solution for any real world problem. In this task, aggregation operators are playing an important role in all the fields. Since most of the realistic problems have uncertainty in nature, one can use the logic of fuzzy and neutrosophic theory. For the entire proposed concepts interval based logic has been used as it handles more uncertainty.
Computational Intelligence
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Author : Leszek Rutkowski
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-05-24
Computational Intelligence written by Leszek Rutkowski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-24 with Technology & Engineering categories.
This quite simply superb book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. These techniques are today commonly applied to issues of artificial intelligence. The book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next up, various neural network architectures are presented and their learning algorithms are derived. Then, the family of evolutionary algorithms is discussed, including connections between these techniques and neural networks and fuzzy systems. Finally, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared.
Recent Advances On Hybrid Approaches For Designing Intelligent Systems
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Author : Oscar Castillo
language : en
Publisher: Springer
Release Date : 2014-03-26
Recent Advances On Hybrid Approaches For Designing Intelligent Systems written by Oscar Castillo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-26 with Technology & Engineering categories.
This book describes recent advances on hybrid intelligent systems using soft computing techniques for diverse areas of application, such as intelligent control and robotics, pattern recognition, time series prediction and optimization complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of type-2 fuzzy logic, which basically consists of papers that propose new models and applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application. The third part contains papers that deal with new models and applications of neural networks in real world problems. The fourth part contains papers with the theme of intelligent optimization methods, which basically consider the proposal of new methods of optimization to solve complex real world optimization problems. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.