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Incomplete fuzzy data processing systems using artificial neural networkIn this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.
Document ID
19930020389
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Patyra, Marek J.
(Minnesota Univ. Duluth, MN, United States)
Date Acquired
September 6, 2013
Publication Date
December 1, 1992
Publication Information
Publication: NASA. Johnson Space Center, North American Fuzzy Logic Processing Society (NAFIPS 1992), Volume 2
Subject Category
Theoretical Mathematics
Accession Number
93N29578
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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