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- W2378441166 abstract "In the recent years, artificial neural networks (ANN) have been widely used to monitor and control the process abnormal pattern occurred especially in the complex manufacturing quality control. But literatures show that this kind of work is primarily addressed according to the developer's personal experiences which would cost too much time with lower recognition accuracy. This paper proposes to use probability neural network (PNN) to recognize the six typical kinds of control chart patterns of the process to improve the design efficiency of the NN pattern recognizer. Research and numerical simulation result shows that PNN has not only the feature of simpler topology structure but also the higher pattern recognition accuracy." @default.
- W2378441166 created "2016-06-24" @default.
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- W2378441166 date "2009-01-01" @default.
- W2378441166 modified "2023-09-24" @default.
- W2378441166 title "Control Chart Pattern Recognition Based on PNN" @default.
- W2378441166 hasPublicationYear "2009" @default.
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