Abstract
Although pattern recognition techniques have been widely applied to identify abnormal patterns in control charts, abnormal parameter value is difficult to be estimated. A pattern recognition system should better have capability to estimate abnormal parameter. In this paper, we present radial basis function (RBF) neural networks for parameter estimation of abnormal control chart patterns. This created control chart pattern recognition system presents good abilities for the estimation of abnormal parameter. We use several examples to demonstrate its usefulness and effectiveness.
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