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| Prediction and Optimization of Leaching Rate during Alkali Boiling Process |
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Received:November 25, 2015
Revised:November 27, 2015
Accepted:December 01, 2015
Published Online:April 18, 2016
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| DOI：doi：10.3969/j.issn.1007-7545.2016.05.008 |
| KeyWord:leaching rate; mechanism model; LS-SVM; PSO algorithm; optimization model |
| Author | Institution |
| LIU Fei-fei |
江西理工大学电气工程与自动化学院 |
| LUO Xian-ping |
江西理工大学机电工程学院 |
| GU Shuai-qi |
江西理工大学机电工程学院 |
| XIN Peng-wu |
江西理工大学机电工程学院 |
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| Abstract: |
| A parallel hybrid model combined with dynamic mechanism model and LS-SVM was built to predict WO3 leaching rate during tungsten alkali boiling process. Based on this hybrid model, alkali boiling process optimization model was established to transform dynamic leaching problem into constrained optimization problem. Then optimization model was solved with particle swarm optimization (PSO) algorithm. The simulation results show that hybrid model has advantages of high prediction accuracy, good performance, high leaching rate of WO3, and low leaching cost. |
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