X̄ control chart pattern identification through efficient off-line neural network training
Hwarng, H.Brian Hubele, Norma Faris
Hubele, Norma Faris
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Abstract
Back-propagation pattern recognizers (BPPR) are proposed to identify unnatural pattern exhibited on Shewhart control charts. In this paper an off-line analysis is performed to investigate the training and learning speed of these BPPRs on simulated x data. The best configuration of the network is further tested to demonstrate the classification capability of the proposed BPPR.
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IIE Transactions (Institute of Industrial Engineers)
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Date
1993
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Article