چکیده مقاله
Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in the manufacturing processes This paper presents a novel hybrid intelligent method for recognition of common types of control chart patterns CCPs The proposed method includes three main modules: the feature extraction module, the classifier module and the optimization module In the feature extraction module, a proper set of the shape features and statistical features are proposed as the efficient characteristic of the patterns In the classifier module, adaptive neuro fuzzy inference system ANFIS is investigated In ANFIS training, the vector of radius has very important role for its recognition accuracy Therefore, in the optimization module, particle swarm optimization PSO algorithm is proposed for finding the optimum vector of radius Simulation results show that the proposed system has high recognition accuracy
کلیدواژهها
نویسندگان
Hossein Babaee
Babol Noshirvani University
Ali Lari
Babol Noshirvani University
Javad Ganjipour
Babol Noshirvani University
Jalil Addeh
Babol Noshirvani University
شیوه ارجاع
Babaee, Hossein and Lari, Ali and Ganjipour, Javad and Addeh, Jalil,1394,Control Chart Patterns Recognition Using Fuzzy Rules and Efficient Features,International Conference on New Research Findings in Electrical Engineering and Computer Science,Tehran
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