Sen Fuzzy Logic and Hydrological Modeling

1. Auflage 2010
ISBN: 978-1-4398-0940-2
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 348 Seiten

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.

Zielgruppe

Graduate students in water resources engineering, earth sciences, agriculture, irrigation, and other geophysical sciences; hydrologists, hydrogeologists, hydraulic engineers, and technicians employed in consulting offices, industry, and government; water resources researchers working in governmental agencies, institutions, universities, and industry.

Autoren/Hrsg.

Sen, Zekai

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Geowissenschaften Geologie Hydrologie, Hydrogeologie
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

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

Über Autor(innen)

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