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

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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.
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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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