Fuzzy Reasoning in Decision Making and Optimization / Edition 1

by Christer Carlsson, Robert Fuller

Overview

Many decision-making tasks are too complex to be understood quantitatively, however, humans succeed by using knowledge that is imprecise rather than precise. Fuzzy logic resembles human reasoning in its use of imprecise information to generate decisions. Unlike classical logic which requires a deep understanding of a system, exact equations, and precise numeric values, fuzzy logic incorporates an alternative way of thinking, which allows modeling complex systems using a higher level of abstraction originating from our knowledge and experience. Fuzzy logic allows expressing this knowledge with subjective concepts such as very big and a long time which are mapped into exact numeric ranges. Since knowledge can be expressed in a more natural by using fuzzy sets, many decision (and engineering) problems can be greatly simplified. Fuzzy logic provides an inference morphology that enables approximate human reasoning capabilities to be applied to knowledge-based systems. The theory of fuzzy logic provides a mathematical strength to capture the un­ certainties associated with human cognitive processes, such as thinking and reasoning. The conventional approaches to knowledge representation lack the means for representating the meaning of fuzzy concepts. As a consequence, the approaches based on first order logic do not provide an appropriate conceptual framework for dealing with the representation of commonsense knowledge, since such knowledge is by its nature both lexically imprecise and non­ categorical.

Product Details

ISBN-13:	9783790824971
Publisher:	Physica-Verlag HD
Publication date:	12/15/2010
Series:	Studies in Fuzziness and Soft Computing , #82
Edition description:	Softcover reprint of hardcover 1st ed. 2002
Pages:	338
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Fuzzy Sets and Fuzzy Logic.- Fuzzy Multicriteria Decision Making.- Fuzzy Reasoning.- Fuzzy Optimization.- Fuzzy Reasoning for Fuzzy Optimization.- Applications to Management.- Future Trends in Fuzzy Reasoning and Fuzzy Decision Making.- Index.