19 July 2013 Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining
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Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88781F (2013) https://doi.org/10.1117/12.2031626
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China
Abstract
To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.
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Yanpo Song, Yanpo Song, Xiaoqi Peng, Xiaoqi Peng, Ying Tang, Ying Tang, Zhikun Hu, Zhikun Hu, } "Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88781F (19 July 2013); doi: 10.1117/12.2031626; https://doi.org/10.1117/12.2031626
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