A NEURO-FUZZY CLASSIFICATION SYSTEM FOR PATTERN RECOGNlTION OF CONTROL CHARTS | ||||
| ERJ. Engineering Research Journal | ||||
| Article 5, Volume 24, Issue 3, July 2001, Page 53-67 PDF (739.67 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2001.71049 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Hindi A. Al-Hindi | ||||
| Associate Professor, Department of Quantitative Methods, College of Business and Economics, King Saud ll niversity , Al-Qasseem | ||||
| Abstract | ||||
| In the past years. neuro-fiuy systems received an increasing attention and were used to solve a wide range of problelix in different domains. A ne~u-o-fiwq S~S~CIII is a hybrid system consisting of an artificial neural network and a fi~zzy inference system where the learning algorithm of the artificial neural network is ilsed lo adjust the parameters of the membership functions associated with the fuzzy inference system. This paper proposes a neuro-fi~uy classification approach for identifying control chart patterns in order to uncover the behavior of the production process. The proposed approach was implemented by building a neuro-f~wy classification system and b\z using simulated data. Nunierical results showed that the proposcd approach has a good recognition periormancc of patterns on control charts. | ||||
| Keywords | ||||
| Neuro-Fuzzy System; Control Chart; Pattern Recognition | ||||
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