Use of reliability measures to improve the performance of Fuzzy ARTMAP networks

P. Ramuhalli, L. Udpa, S. S. Udpa

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

Neural network based signal classification systems are being applied increasingly in non-destructive evaluation to solve the inverse problem. In general, two issues not usually addressed are (i) estimation of reliability measures of the network decision and (ii) ability of the network to learn and improve its performance with time. This paper presents a signal classification systems using the Fuzzy ARTMAP network. Fuzzy logic based reliability measures are developed for the Fuzzy ARTMAP network and used as a feedback for retraining the network to improve its performance. The performance of the algorithm is demonstrated using ultrasonic data obtained from the inspection of welds in nuclear power plant piping.

Original languageEnglish
Pages4015-4020
Number of pages6
StatePublished - 1999
Externally publishedYes
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: Jul 10 1999Jul 16 1999

Conference

ConferenceInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period07/10/9907/16/99

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