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Abstract and Applied Analysis
Volume 2013 (2013), Article ID 386757, 10 pages
Hybrid Artificial Neural Networks Modeling for Faults Identification of a Stochastic Multivariate Process
Department of Statistics and Information Science, Fu Jen Catholic University, No. 510, Zhongzheng Road, Xinzhuang, New Taipei City 24205, Taiwan
Received 7 October 2013; Revised 5 November 2013; Accepted 5 November 2013
Academic Editor: Shen Yin
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 [4 citations]
The following is the list of published articles that have cited the current article.
- Yuehjen E. Shao, Chi-Jie Lu, and Chia-Ding Hou, “Hybrid Soft Computing Schemes for the Prediction of Import Demand of Crude Oil in Taiwan,” Mathematical Problems in Engineering, vol. 2014, pp. 1–11, 2014.
- Yuehjen E. Shao, “Body Fat Percentage Prediction Using Intelligent Hybrid Approaches,” The Scientific World Journal, vol. 2014, pp. 1–8, 2014.
- 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.
- Yuehjen E. Shao, and Ke-Shan Lin, “Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach,” Discrete Dynamics in Nature and Society, vol. 2015, pp. 1–7, 2015.