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Books > Computing & IT > Applications of computing > Artificial intelligence
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Hybrid Self-Organizing Modeling Systems (Paperback, Softcover reprint of hardcover 1st ed. 2009)
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Hybrid Self-Organizing Modeling Systems (Paperback, Softcover reprint of hardcover 1st ed. 2009)
Series: Studies in Computational Intelligence, 211
Expected to ship within 10 - 15 working days
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Models form the basis of any decision. They are used in di?erent
context and for di?erent purposes: for identi?cation, prediction,
classi?cation, or control of complex systems. Modeling is done
theory-driven by logical-mathematical methods or data-driven based
on observational data of the system and some algorithm or software
for analyzing this data. Today, this approach is s- marized as Data
Mining. There are many Data Mining algorithms known like Arti?cial
Neural N- works, Bayesian Networks, Decision Trees, Support Vector
Machines. This book focuses on another method: the Group Method of
Data Handling. -
thoughthismethodologyhasnotyetbeenwellrecognizedintheinternational
science community asa verypowerfulmathematicalmodeling andknowledge
extraction technology, it has a long history. Developed in
1968bythe Ukrainianscientist A.G. Ivakhnenko it combines the
black-box approach and the connectionism of Arti?cial Neural
Networks with well-proven Statistical Learning methods and with
more behavior- justi?ed elements of inductive
self-organization.Over the past 40 years it has been improving and
evolving, ?rst by works in the ?eld of what was known in the U.S.A.
as Adaptive Learning Networks in the 1970s and 1980s and later by
signi? cantcontributions from scientists from Japan,China, Ukraine,
Germany. Many papers and books have been published on this modeling
technology, the vast majority of them in Ukrainian and Russian
language.
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