Explaining relationships between coke quality index and coal properties by Random Forest method

被引:64
|
作者
Chelgani, S. Chehreh [1 ]
Matin, S. S. [2 ]
Hower, James C. [3 ]
机构
[1] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
[2] Islamic Azad Univ, Sci & Res Branch, Environm & Energy Dept, Tehran, Iran
[3] Univ Kentucky, Ctr Appl Energy Res, 2540 Res Pk Dr, Lexington, KY 40511 USA
关键词
Coke quality; Swelling index; Coal rank; Random forest; Variable importance; GROSS CALORIFIC VALUE; VARIABLE IMPORTANCE; MULTIVARIABLE REGRESSION; PREDICTION; CLASSIFICATION; PYROLYSIS; MACERALS; REQUIREMENTS; GRINDABILITY; TECHNOLOGY;
D O I
10.1016/j.fuel.2016.06.034
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this study was shown that random forest (RF) can be used as a sensible new data mining tool for variable importance measurements (VIMs) through various coal properties for prediction of coke quality (Free Swelling Index (FSI)). The VIMs of RF within coal analyses (proximate, ultimate, and petrographic analyses) were applied for the selection of the best predictors of FSI over a wide range of Kentucky coal samples. VIMs assisted by Pearson correlation through proximate, ultimate, and petrographic analyses indicated that volatile matter, carbon, vitrinite, and R-max (coal rank parameters) are the most effective variables for the prediction of FSI. These important predictors have been used as inputs of RF model for the FSI prediction. Outputs in the testing stage of the model indicated that RF can predict FSI quite satisfactorily; the R-2 was 0.93 and mean square error from actual FSIs was 0.15 (had less than interval unit of FSI; 0.5). According to the result, by providing nonlinear inter-dependence approximation among parameters for variable selection and also non-parametric predictive model RF can potentially be further employed as a reliable and accurate technique for the determination of complex relationship through fuel and energy investigations. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:754 / 760
页数:7
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