The book contains ten chapters as follows, Prepare Knowledge, Regression and Self-regression Models with Fuzzy Coefficients; Regression and Self-regression Models with Fuzzy Variables, Fuzzy Input/output Model, Fuzzy Cluster Analysis and Fuzzy Recognition, Fuzzy Linear Programming, Fuzzy Geometric Programming, Fuzzy Relative Equation and Its Optimizing, Interval and Fuzzy Differential Equations and Interval and Fuzzy Functional and Their Variation.
It can not only be used as teaching materials or reference books for under-graduates in higher education, master graduates and doctor graduates in the courses of applied mathematics, computer science, artificial intelligence, fuzzy information process and automation, operations research, system science and engineering, and the like, but also serves as a reference book for researchers in these fields, particularly, for researchers in soft science.
Rezensionen / Stimmen
From the reviews:
"Fuzzy modeling and fuzzy optimization come with a significant diversity expressed in terms of the underlying concepts, methodologies, and algorithms. The book consists of 10 chapters and naturally splits into six parts. . Overall, the book is an interesting and useful reading exploring the wealth and capabilities of fuzzy sets in the framework of system modeling and system optimization." (Witold Pedrycz, Zentralblatt MATH, Vol. 1196, 2010)
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Illustrationen
26
26 s/w Abbildungen
350 p. 26 illus.
ISBN-13
978-3-642-10712-2 (9783642107122)
DOI
10.1007/978-3-642-10712-2
Schweitzer Klassifikation
Prepare Knowledge.- Regression and Self-regression Models with Fuzzy Coefficients.- Regression and Self-regression Models with Fuzzy Variables.- Fuzzy Input-Output Model.- Fuzzy Cluster Analysis and Fuzzy Recognition.- Fuzzy Linear Programming.- Fuzzy Geometric Programming.- Fuzzy Relative Equation and Its Optimizing.- Interval and Fuzzy Differential Equations.- Interval and Fuzzy Functional and their Variation.
