Stability evaluation of dump slope using artificial neural network and multiple regression

被引:0
|
作者
Ashutosh Kumar Bharati
Arunava Ray
Manoj Khandelwal
Rajesh Rai
Ashok Jaiswal
机构
[1] Indian Institute of Technology (BHU) Varanasi,Department of Mining Engineering
[2] Federation University Australia,School of Engineering, Information Technology and Physical Sciences
来源
Engineering with Computers | 2022年 / 38卷
关键词
Multiple regression analysis; Artificial neural network; Finite element method; Dragline dumps;
D O I
暂无
中图分类号
学科分类号
摘要
The present paper focuses on designing an artificial neural network (ANN) model and a multiple regression analysis (MRA) that could be used to predict factor of safety of dragline dump slope. To implement these two models, the dataset was utilized from the numerical simulation results of dragline dump slopes, wherein 216 dragline dump slope models were simulated using a numerical modeling technique employed with the finite element method. The finite element model was incorporated a combination of three geometrical parameters, namely, coal-rib height (Crh), dragline dump slope height (Sh), and dragline dump slope angle (Sa) of the dump slope. The predicted results derived from the MRA and ANN models were compared with the results obtained from the numerical simulation of the dump slope models. Moreover, to compare the validity of both the models, various performance indicators, such as variance account for (VAF), determination coefficient (R2), root mean square error (RMSE), and residual error were calculated. Based on these performance indicators, the ANN model has shown a higher prediction accuracy than the MRA model. The study reveals that the ANN model developed in this research could be handy in designing the dragline dump slopes at the preliminary stage.
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页码:1835 / 1843
页数:8
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