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Fuzzy Logic and Hydrological Modeling

Autor Zekai Sen
en Limba Engleză Hardback – 14 oct 2009
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.
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Specificații

ISBN-13: 9781439809396
ISBN-10: 1439809399
Pagini: 352
Ilustrații: 248 b/w images, 53 tables and 335
Dimensiuni: 156 x 234 x 22 mm
Greutate: 0.61 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press

Public țintă

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.

Cuprins

Introduction. Linguistic Variables and Logic. Fuzzy Sets, Membership Functions, and Operations. Fuzzy Numbers and Arithmetics. Fuzzy Associations and Clusters. Fuzzy Logical Rules. Fuzzy Inference Systems (FIS). Fuzzy Modeling of Hydrological Cycle Elements. Fuzzy Water Resources Operation.

Notă biografică

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

Descriere

The hydrological sciences typically present grey or fuzzy information, making them a choice challenge for fuzzy logic application. An authoritative resource on 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 eliminate 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.