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The Scientific World Journal
Volume 2014 (2014), Article ID 262368, 12 pages
http://dx.doi.org/10.1155/2014/262368
Research Article

Improved GSO Optimized ESN Soft-Sensor Model of Flotation Process Based on Multisource Heterogeneous Information Fusion

1School of Electronic and Information Engineering, University of Science & Technology Liaoning, Anshan 114044, China
2National Financial Security and System Equipment Engineering Research Center, University of Science & Technology Liaoning, Anshan 114044, China

Received 19 February 2014; Accepted 18 March 2014; Published 10 April 2014

Academic Editors: P. Agarwal and V. Bhatnagar

Copyright © 2014 Jie-sheng Wang et al. 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 [3 citations]

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

  • Ivana Jovanović, Igor Miljanović, and Tomislav Jovanović, “Soft computing-based modeling of flotation processes – A review,” Minerals Engineering, vol. 84, pp. 34–63, 2015. View at Publisher · View at Google Scholar
  • Jie-Sheng Wang, and Shuang Han, “Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm,” Computational Intelligence and Neuroscience, vol. 2015, pp. 1–10, 2015. View at Publisher · View at Google Scholar
  • Rohit Salgotra, Urvinder Singh, and Sriparna Saha, “New Cuckoo Search Algorithms with Enhanced Exploration and Exploitation Properties,” Expert Systems with Applications, 2017. View at Publisher · View at Google Scholar