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The Scientific World Journal
Volume 2014, Article ID 383910, 8 pages
http://dx.doi.org/10.1155/2014/383910
Research Article

Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

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

Received 24 December 2013; Accepted 15 January 2014; Published 2 March 2014

Academic Editors: D.-C. Lou and P. Melin

Copyright © 2014 Yuehjen E. Shao. 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. 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
  • Tamás Ferenci, and Levente Kovács, “Predicting body fat percentage from anthropometric and laboratory measurements using artificial neural networks,” Applied Soft Computing, 2017. View at Publisher · View at Google Scholar
  • Karthikeyan, and Balakrishnan, “Feature selection using meta heuristic algorithm for human age estimation,” Journal of Computational and Theoretical Nanoscience, vol. 14, no. 5, pp. 2495–2500, 2017. View at Publisher · View at Google Scholar