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Record 27 of 3316
Incomplete fuzzy data processing systems using artificial neural network
Author and Affiliation:
Patyra, Marek J.(Minnesota Univ., Duluth, MN, United States)
Abstract: In 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.
Publication Date: Dec 01, 1992
Document ID:
19930020389
(Acquired Dec 28, 1995)
Accession Number: 93N29578
Subject Category: THEORETICAL MATHEMATICS
Document Type: Conference Paper
Publication Information: NASA. Johnson Space Center, North American Fuzzy Logic Processing Society (NAFIPS 1992), Volume 2; p. p 565-574
Publisher Information: United States
Financial Sponsor: NASA; United States
Organization Source: Minnesota Univ.; Dept. of Computer Engineering.; Duluth, MN, United States
Description: 10p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: No Copyright
NASA Terms: BINARY DATA; DATA PROCESSING; DATA PROCESSING EQUIPMENT; FUZZY SYSTEMS; NEURAL NETS; APPROXIMATION; DATA RETRIEVAL; ERRORS
Imprint And Other Notes: In NASA. Johnson Space Center, North American Fuzzy Logic Processing Society (NAFIPS 1992), Volume 2 p 565-574 (SEE N93-29556 11-59)
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