Control chart pattern recognition using K-MICA clustering and neural networks

► An intelligent system for recognition of control chart patterns is proposed. ► The proposed system includes two main modules: a clustering module and a classifier module. ► The clustering module is a suitable combination of the modified imperialist competitive algorithm and the K-means algorithm. ► Simulation results confirm that the proposed system outperforms other systems and show high recognition accuracy, about 99.65%.