1st Edition

Fuzzy Logic and Hydrological Modeling

By Zekai Sen Copyright 2010
    348 Pages 248 B/W Illustrations
    by CRC Press

    352 Pages 248 B/W Illustrations
    by CRC Press

    The hydrological sciences typically present grey or fuzzy information, making them quite messy and a choice challenge for fuzzy logic application. Providing readers with the first book to cover fuzzy logic modeling as it relates to water science, the author takes an approach that incorporates verbal expert views and other parameters that allow him to eschew the use of mathematics. The book’s first seven chapters expose the fuzzy logic principles, processes and design for a fruitful inference system with many hydrological examples. The last two chapters present the use of those principles in larger scale hydrological scales within the hydrological cycle.

    Introduction

    General

    Fuzziness in Hydrology

    Why Use Fuzzy Logic in Water Sciences?

    References

    Problems

    Linguistic Variables and Logic

    General

    Words

    Linguistic Variables

    Scientific Sentences

    Fuzzy Scales

    Fuzzy Logic Thinking Stages

    Approximate Reasoning

    References

    Problems

    Fuzzy Sets, Membership Functions, and Operations

    General

    Crisp and Fuzzy Sets in Hydrology

    Formal Fuzzy Sets

    Membership Functions

    Membership Function Allocation

    Hedges (Adjectivized Words)

    Logical Operations on Fuzzy Sets

    References

    Problems

    Fuzzy Numbers and Arithmetics

    General

    Fuzzy Numbers

    Fuzzy Addition

    Fuzzy Subtraction

    Fuzzy Multiplication

    Fuzzy Division

    Extremes of Fuzzy Numbers

    Extension Principle

    References

    Problems

    Fuzzy Associations and Clusters

    General

    Crisp to Fuzzy Relationships

    Logical Relationships

    Fuzzy Logic Relations

    Fuzzy Compositions

    Logical Categorization

    Fuzzy Clustering Algorithms

    References

    Problems

    Fuzzy Logical Rules

    General

    Fuzzification

    “IF . . . THEN . . .” Rules

    Fuzzy Proposition

    Input Rule Base Establishment

    Complete Rule Base

    References

    Problems

    FIS

    General

    Fuzzy Inference Systems (FIS)

    Mamdani FIS

    Defuzzification

    Sugeno FIS

    Tsukamoto FIS

    S¸ en FIS

    FIS Training

    Triple Variable Fuzzy Systems

    Adaptive-Network-Based FIS (ANFIS)

    References

    Problems

    Fuzzy Modeling of Hydrological Cycle Elements

    General

    Simple Evaporation Modeling

    Infiltration Rate Model

    Rainfall Amount Prediction

    Rainfall–Runoff Relationship

    Rainfall–Groundwater Recharge

    Fuzzy Aquifer Classification Chart

    River Traffic Model

    References

    Fuzzy Water Resources Operation

    General

    Fuzzy Water Budget

    Drinking Water Consumption Prediction

    Fuzzy Volume Change in Reservoir Storage

    Crisp and Fuzzy Dynamic Programming

    Multiple Reservoir Operation Rule

    Lake Level Estimation

    Triple Diagrams Rule Base

    Logical-Conceptual Models

    References

    Biography

    Zekai Sen is a member of the Department of Civil Engineering at the Technical University of Istanbul.