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Analysis and Synthesis of Fuzzy Control Systems

for later chapters, which cover: T-S fuzzy modeling and identification via nonlinear models or data Stability analysis of T-S;

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Analysis and Synthesis of Fuzzy Control Systems

for later chapters, which cover: T-S fuzzy modeling and identification via nonlinear models or data Stability analysis of T-S;

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Model Free Adaptive Fuzzy Control

of such processes. The book discusses one particular approach to the fuzzy controllers. Adaptive Model Free Fuzzy Control is a goal oriented;

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Model Based Fuzzy Control

Model Based Fuzzy Control uses a given conventional or fuzzy open loop model of the plant under control to derive the set of fuzzy rules;

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Modern Control Engineering

recent methods in system identification and optimal, digital, adaptive, robust, and fuzzy control, as well as stability, controllability;

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Fuzzy Model Identification

During the past few years two principally different approaches to the design of fuzzy controllers have emerged: heuristics-based design and;

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Interpretability of Computational Intelligence Based Regression Models

The key idea of this book is that hinging hyperplanes, neural networks and support vector machines can be transformed into fuzzy models;

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Fuzzy Control Systems Design And Analysis

A comprehensive treatment of model-based fuzzy control systems This volume offers full coverage of the systematic framework for the;

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Policy Decision Modeling with Fuzzy Logic

Simulation Model (PODESIM). This computational model is a multi-level fuzzy inference system that allows the identification of the decision emergence;

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Modeling Fuzzy Spatiotemporal Data with XML

This book offers in-depth insights into the rapidly growing topic of technologies and approaches to modeling fuzzy spatiotemporal data with;

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Modeling Fuzzy Spatiotemporal Data with XML

This book offers in-depth insights into the rapidly growing topic of technologies and approaches to modeling fuzzy spatiotemporal data with;

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Biological Models via Interval Type-2 Fuzzy Sets

in biological modeling. Interval type-2 fuzzy modeling is a comparatively recent direction of research in fuzzy modeling. As the modeling of biological;

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Fuzzy Probabilities and Fuzzy Sets for Web Planning

. In part two, Chapters 4-10, we use fuzzy probabilities to model a fuzzy queuing system . We switch to employ ing fuzzy arrival rates and fuzzy;

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System Identification and Adaptive Control

research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both;

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Fuzzy C-means Clustering using Pattern Recognition

as the identification of a probabilistic model which provides the explanation of the process generating the data clarity seen and so on;

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Fuzzy Arbitrary Order System Fuzzy Fract

Presents a systematic treatment of fuzzy fractional differential equations as well as newly developed computational methods to model;

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Fuzzy Control and Identification

unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example;

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Soft Computing with NeuroFuzzy Systems

This book covers different topics from soft computing and neuro-fuzzy systems, including intelligent neuro-fuzzy models, adaptive neuro;

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Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems

This book aims to introduce the state-of-the-art research of stability/performance analysis and optimal synthesis methods for fuzzy-model;

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Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems

This book aims to introduce the state-of-the-art research of stability/performance analysis and optimal synthesis methods for fuzzy-model;

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Fuzzy-AI Model and Big Data Exploration

Based on the idea of a universal rule for problem solving, the book suggests that the System-Fuzzy Approach (SFA) Model can be applied to;

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An Introduction to Fuzzy Sets

of uncertainties in oil fields and oil production to make a decision as to what model is best in such a fuzzy environment. Additionally, several challenges;

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Fuzzy Hierarchical Model for Risk Assessment

Model for Risk Assessment introduces a fuzzy-based hierarchical approach to solve risk management problems considering both qualitative and;

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Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration

Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved;

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Deep Neuro-Fuzzy Systems with Python

Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current;

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Fuzzy Differential Equations and Applications for Engineers and Scientists

Differential equations play a vital role in the modeling of physical and engineering problems, such as those in solid and fluid mechanics;

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Protein Secondary Structure Prediction

-Fuzzy Inference System (ANFIS) based model for predicting helical transmembrane region by acquiring the structural information of target protein;

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