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Books > Computing & IT > Applications of computing > Artificial intelligence
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Computational Intelligence Systems and Applications - Neuro-Fuzzy and Fuzzy Neural Synergisms (Paperback, Softcover reprint of the original 1st ed. 2002)
Loot Price: R4,033
Discovery Miles 40 330
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Computational Intelligence Systems and Applications - Neuro-Fuzzy and Fuzzy Neural Synergisms (Paperback, Softcover reprint of the original 1st ed. 2002)
Series: Studies in Fuzziness and Soft Computing, 86
Expected to ship within 18 - 22 working days
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Traditional Artificial Intelligence (AI) systems adopted symbolic
processing as their main paradigm. Symbolic AI systems have proved
effective in handling problems characterized by exact and complete
knowledge representation. Unfortunately, these systems have very
little power in dealing with imprecise, uncertain and incomplete
data and information which significantly contribute to the
description of many real world problems, both physical systems and
processes as well as mechanisms of decision making. Moreover, there
are many situations where the expert domain knowledge (the basis
for many symbolic AI systems) is not sufficient for the design of
intelligent systems, due to incompleteness of the existing
knowledge, problems caused by different biases of human experts,
difficulties in forming rules, etc. In general, problem knowledge
for solving a given problem can consist of an explicit knowledge
(e.g., heuristic rules provided by a domain an implicit, hidden
knowledge "buried" in past-experience expert) and numerical data. A
study of huge amounts of these data (collected in databases) and
the synthesizing of the knowledge "encoded" in them (also referred
to as knowledge discovery in data or data mining), can
significantly improve the performance of the intelligent systems
designed."
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