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Books > Business & Economics > Business & management > Management & management techniques > Operational research
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Fuzzy Reasoning in Decision Making and Optimization (Paperback, Softcover reprint of hardcover 1st ed. 2002)
Loot Price: R4,592
Discovery Miles 45 920
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Fuzzy Reasoning in Decision Making and Optimization (Paperback, Softcover reprint of hardcover 1st ed. 2002)
Series: Studies in Fuzziness and Soft Computing, 82
Expected to ship within 10 - 15 working days
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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 informa tion to generate
decisions. Unlike classical logic which requires a deep under
standing 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 con ceptual framework for dealing with the
representation of commonsense knowl edge, since such knowledge is
by its nature both lexically imprecise and non categorical."
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