Fuzzy logic for the management of uncertainty
By: edited by Lotfi A. Zadeh, Janusz Kacprzyk.
Contributors: Zadeh, Lotfi Asker.; Kacprzyk, Janusz.
Publisher: Wiley
Published: 1992
Place of publication: New York
Language: eng
Number of pages: 676
Subjects: Artificial intelligence.; Fuzzy systems.
Description: "Fuzzy systems are mathematically based systems that enable computers to handle vague, imprecise, or ambiguous information. Edited by two of the top names in this field and written by a team of international experts, here is the most up-to-date and complete compilation of articles in fuzzy logic research. All chapters are original works prepared specifically for this volume, including articles on applications and tools.^

Fuzzy Logic for the Management of Uncertainty covers many important topics, including:" "Developments in mathematics that have paved the road for fuzzy logic;" "Deep, and of a broad perspective, exposition of virtually all approaches used in contemporary science for the representation and handling of imperfect (uncertain, imprecise, vague, ambiguous, etc.) information;" "Coverage of practically all relevant and promising directions and approaches in fuzzy logic research including LT--fuzzy logic, model theoretic approaches, intuitionistic fuzzy logic, nonmonotonic fuzzy logic, modifier fuzzy logic;" "VLSI fuzzy logic-based chips that have triggered the implementation of fuzzy logic in so many fields of science and technology;" "A broad coverage of fuzzy logic in approximate reasoning, including basic issues related to the role of fuzzy logic for approximate reasoning, analyses of various definitions of fuzzy implication that is a crucial element in fuzzy logic-based reasoning schemes,^

general issues related to reasoning and inference based on fuzzy logic, inconsistencies and explanations in imprecise reasoning and databases;" "Use of fuzzy logic for knowledge representation, including the use of fuzzy relations, fuzzy linguistic modifiers, etc.;" "Use of fuzzy logic for knowledge acquisition and elicitation, mainly for machine learning;" "Use of fuzzy logic for the modelling of neurons and neural networks;" "Use of fuzzy logic for the development of fuzzified higher level computer languages, notably for the fuzzification of LISP;" "Use of fuzzy logic for the management of uncertainty in implemented knowledge-based systems;" "Use of fuzzy logic for the validation of knowledge-based systems;" "Use of fuzzy logic in intelligent database management systems." --Book Jacket.
Notes: Includes bibliographical references and index.