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Proceedings Paper

Connectionist approach to adaptive reasoning
Author(s): Mohan S. Reddy; Abhijit S. Pandya; D. V. Reddy
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Paper Abstract

This paper illustrates the neural net approach to constructing a fuzzy logic decision system. This technique employs an artificial neural network (ANN) to recognize the relationships that exist between the various inputs and outputs. An ANN is constructed based on the variable present in the application. The network is trained and tested. After successful testing, the ANN is exposed to new data and the results are grouped into fuzzy membership sets. This data grouping forms the basis of a new ANN. The network is now trained and tested with the fuzzy membership data. New data is presented to the trained network and the results from the fuzzy implications. This approach is used to compute skid resistance values from G-analyst accelerometer readings on open grid bridge decks.

Paper Details

Date Published: 13 June 1995
PDF: 15 pages
Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); doi: 10.1117/12.211816
Show Author Affiliations
Mohan S. Reddy, PacifiCare of Florida (United States)
Abhijit S. Pandya, Florida Atlantic Univ. (United States)
D. V. Reddy, Florida Atlantic Univ. (United States)


Published in SPIE Proceedings Vol. 2493:
Applications of Fuzzy Logic Technology II
Bruno Bosacchi; James C. Bezdek, Editor(s)

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