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Type 2 Fuzzy Granular Models

is proposed. A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via;

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Biological Models via Interval Type-2 Fuzzy Sets

This book offers a gentle introduction to type-2 fuzzy sets and, in particular, interval type-2 fuzzy sets and their application;

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Hierarchical Type-2 Fuzzy Aggregation of Fuzzy Controllers

This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together;

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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms

their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which;

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Uncertain Rule-Based Fuzzy Logic Systems

fuzzy logic to the next level-type-2 fuzzy logic. It presents a complete development of both type-1 and type-2 fuzzy logic systems, showing how;

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Introduction To Type-2 Fuzzy Logic Control

Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students;

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Edge Detection Methods Based on Generalized Type 2 Fuzzy Logic

In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra;

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

In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed;

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Tracking Performance Of Maglev System Using Type-2 Fuzzy Logic Control

different levels. Lastly for robust performance, disturbance is applied in MLS.For this task we have designed Interval Type-2 Fuzzy Logic Controller;

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Handbook of Granular Computing

contributions from leading experts in the field. * Includes chapters covering the foundations of granular computing, interval analysis and fuzzy set;

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Type 2 Fuzzy Neural Networks and Their Applications

This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination;

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

such as rough sets: the experts speak; generalized rough sets; rough sets and graphs; rough and fuzzy hybridization; granular computing; data;

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Uncertain Rule-Based Fuzzy Systems

The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty - i.e., type-2;

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Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control

Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results;

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Rough Sets, Fuzzy Sets, Data Mining and Granular Computing

This book constitutes the refereed proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular;

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Fuzzy Neural Networks for Real Time Control Applications

AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS

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Cognitive Modeling of Human Memory and Learning

classification of memory tasks by deep learning-based models Proposes two algorithms of type-2 fuzzy reasoning: Interval Type-2 fuzzy reasoning (IT2FR;

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Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical;

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Extension of the Fuzzy Sugeno Integral Based on Generalized Type-2 Fuzzy Logic

This book presents an extension of the aggregation operator of the generalized interval type-2 Sugeno integral using generalized type-2;

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Soft Computing with NeuroFuzzy Systems

recurrent neuro-fuzzy systems for fault prognosis; and neuro-fuzzy model for QoS based selection of web service. Section 2 focuses on adaptive;

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Optimization of Type 2 Fuzzy Controllers Using the Bee Colony Algorithm

trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a;

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Neuro-Fuzzy Equalizers for Mobile Cellular Channels

existing equalizers for wireless channels. It discusses several techniques for channel equalization, including the type-2 fuzzy adaptive filter;

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Neuro-Fuzzy Equalizers for Mobile Cellular Channels

existing equalizers for wireless channels. It discusses several techniques for channel equalization, including the type-2 fuzzy adaptive filter;

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Granular Computing

used to analyze and design intelligent systems, information granules need to be made explicit. An emerging discipline, granular computing;

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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms

. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and;

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Genetic Algorithms, Fuzzy Systems & Website Classification

discussed include genetic algorithm for optimal design of fuzzy classifiers; design and analysis of type-2 fuzzy PI controller; selection of supply;

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New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic

automatic design of classifiers and is focused in the Generalized Type-2 Fuzzy Logic, because the uncertainty handling can provide us with the;

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