Fuzzy Rule-Based Modeling with Applications to Geophysical, Biological, and Engineering Systems: 1st Edition (Hardback) book cover

Fuzzy Rule-Based Modeling with Applications to Geophysical, Biological, and Engineering Systems

1st Edition

By Andras - Bardossy, Lucien Duckstein

CRC Press

256 pages

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Hardback: 9780849378331
pub: 1995-04-28
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This book presents in a systematic and comprehensive manner the modeling of uncertainty, vagueness, or imprecision, alias "fuzziness," in just about any field of science and engineering. It delivers a usable methodology for modeling in the absence of real-time feedback.

The book includes a short introduction to fuzzy logic containing basic definitions of fuzzy set theory and fuzzy rule systems. It describes methods for the assessment of rule systems, systems with discrete response sets, for modeling time series, for exact physical systems, examines verification and redundancy issues, and investigates rule response functions.

Definitions and propositions, some of which have not been published elsewhere, are provided; numerous examples as well as references to more elaborate case studies are also given. Fuzzy rule-based modeling has the potential to revolutionize fields such as hydrology because it can handle uncertainty in modeling problems too complex to be approached by a stochastic analysis. There is also excellent potential for handling large-scale systems such as regionalization or highly non-linear problems such as unsaturated groundwater pollution.

Table of Contents


Basic Elements and Definitions

Fuzzy Sets: Definitions and Properties

Fuzzy Numbers

Assessment of the Membership Functions

Fuzzy Sets, Possibilities and Probabilities

Fuzzy Rules

The Structure of a Fuzzy Rule

Combination of Fuzzy Rule Responses


Case of Fuzzy Premises

Rules with Multiple Responses

Rule Systems

Completeness and Redundancy

Variables to Be Used for Rule Systems

Rules and Continuous Functions

Membership Functions in Rule Systems

Sensitivity of the Response Functions

Rule Construction

Explicit Rule Specification

Deriving Rule Systems from Datasets

Known Rule Structure

Partially Explicit Rule Structures

Unknown Rule Structure

Deriving Rule Systems from Fuzzy Data

Rule Verification

Removing Unnecessary Rules

Fuzzy Rule-Based Modeling versus Fuzzy Control

Principles of Fuzzy Control

Examples of Fuzzy Control

Fuzzy Control and Fuzzy Rule-Based Modeling

Rule Systems with Discrete Responses

Combination of Discrete Consequence Type Rules

Rule Assessment

Application to Weather Classification

Application to Time Series

Rule Assessment

Example: Water Demand Forecasting

Example: Daily Mean Temperature

Application to Dynamical Physical Systems

Application to Soil Water Movement

Other Applications

Application to Medical Diagnosis

Sustainable Reservoir Operation


A Proofs of Selected Propositions

About the Series

Systems Engineering

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Subject Categories

BISAC Subject Codes/Headings:
TECHNOLOGY & ENGINEERING / Engineering (General)
TECHNOLOGY & ENGINEERING / Industrial Engineering