Prediction of the blast-induced ground vibration in tunnel blasting using ANN, moth-flame optimized ANN, and gene expression programming

2021 ◽  
Author(s):  
Abiodun Ismail Lawal ◽  
Sangki Kwon ◽  
Geon Young Kim
2020 ◽  
Vol 61 (5) ◽  
pp. 107-116
Author(s):  
Hoang Nguyen . ◽  
Nam Xuan Bui . ◽  
Hieu Quang Tran . ◽  
Giang Huong Thi Le ◽  

The efforts of this study are to develop and propose a state - of - the - art model for predicting blast - induced ground vibration in open - pit mines with high accuracy anf ability based on the gene expression programming (GEP) technique. 25 blasts were conducted in the Tan Dong Hiep quarry mines with a total of 83 blasting events that were collected for this study. The GEP method was then applied to develop a non - linear equation for predicting blast - induced ground vibration based on a variety of influential parameters. A traditional empirical equation, namely Sadovski, was also applied to compare with the proposed GEP model. The results indicated that the GEP model can predict blast - induced ground vibration in open - pit mines better than the Sadovski model with an RMSE of 0.986 and R2 of 0.867. Meanwhile, the traditional empirical model (Sadovski) only provided an accuracy with an RMSE of 1.850 và R2 of 0.767.


2011 ◽  
Vol 22 (5) ◽  
pp. 899-913 ◽  
Author(s):  
Jiao-Ling ZHENG ◽  
Chang-Jie TANG ◽  
Kai-Kuo XU ◽  
Ning YANG ◽  
Lei DUAN ◽  
...  

2013 ◽  
Vol 45 (6) ◽  
pp. 704-714
Author(s):  
Jinxin QIAN ◽  
Jiayuan YU

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