Journal of Northeastern University Natural Science ›› 2020, Vol. 41 ›› Issue (1): 1-6.DOI: 10.12068/j.issn.1005-3026.2020.01.001

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Optimal Setting for Hydrometallurgical Whole Process Based on Case-Based Reasoning

NIU Da-peng, ZANG Ya-li, JIA Ming-xing   

  1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
  • Received:2019-05-04 Revised:2019-05-04 Online:2020-01-15 Published:2020-02-01
  • Contact: NIU Da-peng
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Abstract: The hydrometallurgical whole process has the characteristics of variable working conditions, strong coupling and non-linearity. The process optimization control based on mechanism model is usually difficult to solve, and has difficulty in adapting to changes in working conditions. Thus, a case-based reasoning(CBR)method to optimize the whole process is proposed. Due to the close coupling in hydrometallurgical the production processes, the operation parameters are related to each other, which shows the relationship between the operation parameters of each working condition and the optimal setting value of each adjustment variable. Therefore, the rules between the optimal setting values of each operation parameter and operation variables are searched by mining the association rules of historical data. The mining rules are used in the case correction to solve the problem that rules are difficult to obtain. The simulation results show that this method can improve the economic benefits of the hydrometallurgical whole process.

Key words: hydrometallurgy, optimal setting, historical data, case-based reasoning(CBR), association rule mining

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