Fuzzy Logic and Hydrological Modeling [Paperback]

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 books 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. 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.

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 books 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.

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