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New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks

2016-06-02 Technology & Engineering
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Release : 2016-06-02
Genre : Technology & Engineering
Kind : eBook
Book Rating : 875/5 ( reviews)

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Book Synopsis New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks by : Fernando Gaxiola

Download or read book New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks written by Fernando Gaxiola. This book was released on 2016-06-02. Available in PDF, EPUB and Kindle. Book excerpt: In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for รด=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.

Recent Developments and the New Direction in Soft-Computing Foundations and Applications

2018-05-28 Technology & Engineering
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Release : 2018-05-28
Genre : Technology & Engineering
Kind : eBook
Book Rating : 084/5 ( reviews)

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Book Synopsis Recent Developments and the New Direction in Soft-Computing Foundations and Applications by : Lotfi A. Zadeh

Download or read book Recent Developments and the New Direction in Soft-Computing Foundations and Applications written by Lotfi A. Zadeh. This book was released on 2018-05-28. Available in PDF, EPUB and Kindle. Book excerpt: This book is an authoritative collection of contributions in the field of soft-computing. Based on selected works presented at the 6th World Conference on Soft Computing, held on May 22-25, 2016, in Berkeley, USA, it describes new theoretical advances, as well as cutting-edge methods and applications. Theories cover a wealth of topics, such as fuzzy logic, cognitive modeling, Bayesian and probabilistic methods, multi-criteria decision making, utility theory, approximate reasoning, human-centric computing and many others. Applications concerns a number of fields, such as internet and semantic web, social networks and trust, control and robotics, computer vision, medicine and bioinformatics, as well as finance, security and e-Commerce, among others. Dedicated to the 50th Anniversary of Fuzzy Logic and to the 95th Birthday Anniversary of Lotfi A. Zadeh, the book not only offers a timely view on the field, yet it also discusses thought-provoking developments and challenges, thus fostering new research directions in the diverse areas of soft computing.

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

2015-06-12 Technology & Engineering
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Release : 2015-06-12
Genre : Technology & Engineering
Kind : eBook
Book Rating : 478/5 ( reviews)

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Book Synopsis Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization by : Patricia Melin

Download or read book Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization written by Patricia Melin. This book was released on 2015-06-12. Available in PDF, EPUB and Kindle. Book excerpt: 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. The book is organized in eight main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents diverse applications of nature-inspired optimization algorithms. The sixth part contains papers describing new optimization algorithms. The seventh part contains papers describing applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. Finally, the eighth part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques.

Recent Advances on Hybrid Approaches for Designing Intelligent Systems

2014-03-26 Technology & Engineering
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Release : 2014-03-26
Genre : Technology & Engineering
Kind : eBook
Book Rating : 709/5 ( reviews)

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Book Synopsis Recent Advances on Hybrid Approaches for Designing Intelligent Systems by : Oscar Castillo

Download or read book Recent Advances on Hybrid Approaches for Designing Intelligent Systems written by Oscar Castillo. This book was released on 2014-03-26. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Recent Advances on Hybrid Intelligent Systems

2012-09-14 Technology & Engineering
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Release : 2012-09-14
Genre : Technology & Engineering
Kind : eBook
Book Rating : 215/5 ( reviews)

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Book Synopsis Recent Advances on Hybrid Intelligent Systems by : Oscar Castillo

Download or read book Recent Advances on Hybrid Intelligent Systems written by Oscar Castillo. This book was released on 2012-09-14. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of 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 groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for achieving efficient pattern recognition or time series prediction. The third part contains papers with the theme of bio-inspired and genetic optimization methods, which basically consider the proposal of new methods and applications of bio-inspired optimization to solve complex optimization of real problems. The fourth part contains papers that deal with the application of intelligent optimization techniques in real world problems in scheduling, planning and manufacturing. 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.

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