Time Series Models Discovery with Similarity-Based Neuro-Fuzzy Networks and Evolutionary Algorithms

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TypeArticle
ConferenceProceedings of the 2002 IEEE World Congress on Computational Intelligence (WCCI'02), May 12-17, 2002., Hawaii, USA
AbstractThe discovery of patterns of dependency in heterogeneous multivariate dynamic systems is approached with similarity-based neuro-fuzzy networks and evolutionary algorithms. Search space contains general auto-regressive non-linear models representing the dependency structure of the process. Examples show that the proposed approach gives better results than the classical statistical one.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number44901
NPARC number8913484
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Record identifier31d9a7b0-f8f9-4666-b468-88b99342d1cf
Record created2009-04-22
Record modified2016-05-09
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