DC Field | Value | Language |
---|---|---|
dc.contributor.author | CHO, SB | ko |
dc.contributor.author | Kim, JinHyung | ko |
dc.date.accessioned | 2009-07-31T05:26:28Z | - |
dc.date.available | 2009-07-31T05:26:28Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 1995-02 | - |
dc.identifier.citation | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, v.25, no.2, pp.380 - 384 | - |
dc.identifier.issn | 0018-9472 | - |
dc.identifier.uri | http://hdl.handle.net/10203/10423 | - |
dc.description.abstract | Recently, in the area of artificial neural networks, the concept of combining multiple networks has been proposed as a new direction for the development of highly reliable neural network systems. In this paper we propose a method for multinetwork combination based on the fuzzy integral. This technique nonlinearly combines objective evidence, in the form of a fuzzy membership function, with subjective evaluation of the worth of the individual neural networks with respect to the decision. The experimental results with the recognition problem of on-line handwriting characters confirm the superiority of the presented method to the other voting techniques. | - |
dc.language | English | - |
dc.language.iso | en_US | en |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | COMBINING MULTIPLE NEURAL NETWORKS BY FUZZY INTEGRAL FOR ROBUST CLASSIFICATION | - |
dc.type | Article | - |
dc.identifier.wosid | A1995QC40700017 | - |
dc.identifier.scopusid | 2-s2.0-0029247604 | - |
dc.type.rims | ART | - |
dc.citation.volume | 25 | - |
dc.citation.issue | 2 | - |
dc.citation.beginningpage | 380 | - |
dc.citation.endingpage | 384 | - |
dc.citation.publicationname | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.contributor.localauthor | Kim, JinHyung | - |
dc.contributor.nonIdAuthor | CHO, SB | - |
dc.type.journalArticle | Letter | - |
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