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Mathematical Problems in Engineering
Volume 2013, Article ID 658630, 6 pages
http://dx.doi.org/10.1155/2013/658630
Research Article

Analyzing Taiwan IC Assembly Industry by Grey-Markov Forecasting Model

Department of Industrial Engineering and Management, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan

Received 14 September 2013; Revised 19 October 2013; Accepted 20 October 2013

Academic Editor: Teen-Hang Meen

Copyright © 2013 Lei-Chuan Lin and Shan-Yau Wu. 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.

  • Chao Wang, Ting-Zhu Huang, and Wai-Ki Ching, “A New Multivariate Markov Chain Model for Adding a New Categorical Data Sequence,” Mathematical Problems in Engineering, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
  • Wei Liu, Shaocheng Zhang, and Chunyang Gao, “Research on the GM(1,1)-Markov chain model of highway freight volume forecasting,” Proceedings of IEEE International Conference on Grey Systems and Intelligent Services, GSIS, vol. 2015-, pp. 307–311, 2015. View at Publisher · View at Google Scholar
  • Yanyan Zheng, Shou Chen, Tong Shu, and Kinkeung Lai, “A study on the forecasting trend of foreign direct investment chain system-Based on the comparison between grey Markov forecasting model and time series forecasting model,” Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, vol. 36, no. 4, pp. 897–999, 2016. View at Publisher · View at Google Scholar
  • Jinli Duan, Feng Jiao, Qishan Zhang, and Zhibin Lin, “Predicting Urban Medical Services Demand in China: An Improved Grey Markov Chain Model by Taylor Approximation,” International Journal of Environmental Research and Public Health, vol. 14, no. 8, pp. 883, 2017. View at Publisher · View at Google Scholar