Parallel algorithm for control chart pattern recognition

Authors: Wani, M.A. and Rashid, S.

Journal: Proceedings - ICMLA 2005: Fourth International Conference on Machine Learning and Applications

Volume: 2005

Pages: 89-93

ISBN: 9780769524955

DOI: 10.1109/ICMLA.2005.51

Abstract:

Fast control chart pattern recognition aids in instantaneous detection of abnormal functioning of a system. In this paper, we present a parallel algorithm for fast control chart pattern recognition. It addresses three major issues of control chart pattern recognition: (i) transparency (ii) accuracy and (iii) fast detection of abnormal patterns. The algorithm uses novel shape features extracted from a control chart pattern (CCP) instead of the unprocessed CCP data or its statistical properties. These shape features can be extracted in parallel. A parallel algorithm that is based on distributed and synergistic neural network structure for recognition of CCPs is described. The paper presents the results of analyzing several hundred control chart patterns and gives a comparison with those reported in previous work. © 2005 IEEE.

Source: Scopus

Preferred by: Mohammad Wani