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Mathematical Problems in Engineering
Volume 2013, Article ID 516760, 7 pages
http://dx.doi.org/10.1155/2013/516760
Research Article

Fault Identification in Industrial Processes Using an Integrated Approach of Neural Network and Analysis of Variance

Department of Statistics and Information Science, Fu Jen Catholic University, 510 Chungcheng Road, Xinzhuang District, New Taipei City 24205, Taiwan

Received 21 November 2012; Revised 28 April 2013; Accepted 14 May 2013

Academic Editor: Jun Zhao

Copyright © 2013 Yuehjen E. Shao and Chia-Ding Hou. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [9 citations]

The following is the list of published articles that have cited the current article.

  • Xiaodan Gu, Fang Deng, and Jie Chen, “Fault identification for the large-scale system using trend analysis,” Proceedings of the 33rd Chinese Control Conference, pp. 3301–3306, . View at Publisher · View at Google Scholar
  • Farshid Keivanian, and Nasser Mehrshad, “Intelligent feature subset selection with unspecified number for body fat prediction based on binary-GA and Fuzzy-Binary-GA,” 2015 2nd International Conference on Pattern Recognition and Image Analysis (IPRIA), pp. 1–7, . View at Publisher · View at Google Scholar
  • Hernan Larralde, “Statistics of the duration time of a random walk given its present position: Dating a random walk,” Physical Review E, vol. 88, no. 6, 2013. View at Publisher · View at Google Scholar
  • Yuehjen E. Shao, and Chia-Ding Hou, “Hybrid Artificial Neural Networks Modeling for Faults Identification of a Stochastic Multivariate Process,” Abstract and Applied Analysis, 2013. View at Publisher · View at Google Scholar
  • Yuehjen E. Shao, “Body Fat Percentage Prediction Using Intelligent Hybrid Approaches,” The Scientific World Journal, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
  • Yuehjen E. Shao, “Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches,” Abstract and Applied Analysis, vol. 2014, pp. 1–9, 2014. View at Publisher · View at Google Scholar
  • Chia-Ding Hou, and Yuehjen E. Shao, “Integrated Use of Statistical-Based Approaches and Computational Intelligence Techniques for Tumors Classification Using Microarray,” Discrete Dynamics in Nature and Society, vol. 2015, pp. 1–8, 2015. View at Publisher · View at Google Scholar
  • Yuehjen E. Shao, “Using a Computational Intelligence Hybrid Approach to Recognize the Faults of Variance Shifts for a Manufacturing Process,” Journal of Industrial and Intelligent Information, 2016. View at Publisher · View at Google Scholar
  • M. Esmail Dehghan Monfared, and Fazlollah Lak, “Bayesian estimation of the change point in a gamma process using X control chart,” Communications in Statistics: Simulation and Computation, vol. 46, no. 3, pp. 2333–2345, 2017. View at Publisher · View at Google Scholar