Estimation of blast-induced peak particle velocity through the improved weighted random forest technique

He, Biao and Lai, Sai Hin and Mohammed, Ahmed Salih and Sabri, Mohanad Muayad Sabri and Ulrikh, Dmitrii Vladimirovich (2022) Estimation of blast-induced peak particle velocity through the improved weighted random forest technique. Applied Sciences-Basel, 12 (10). ISSN 2076-3417, DOI

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Blasting is one of the primary aspects of the mining operations, and its environmental effects interfere with the safety of lives and property. Therefore, it is essential to accurately estimate the environmental impact of blasting, i.e., peak particle velocity (PPV). In this study, a regular random forest (RF) model was developed using 102 blasting samples that were collected from an open granite mine. The model inputs included six parameters, while the output is PPV. Then, to improve the performance of the regular RF model, five techniques, i.e., refined weights based on the accuracy of decision trees and the optimization of three metaheuristic algorithms, were proposed to enhance the predictive capability of the regular RF model. The results showed that all refined weighted RF models have better performance than the regular RF model. In particular, the refined weighted RF model using the whale optimization algorithm (WOA) showed the best performance. Moreover, the sensitivity analysis results revealed that the powder factor (PF) has the most significant impact on the prediction of the PPV in this project case, which means that the magnitude of the PPV can be managed by controlling the size of the PF.

Item Type: Article
Funders: Ministry of Science and Higher Education of the Russian Federation [Grant No: 075-15-2021-1333]
Uncontrolled Keywords: Blasting; Ground vibration; PPV prediction; Random forest; Whale optimization algorithm
Subjects: Q Science > QC Physics
Q Science > QD Chemistry
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering > Department of Civil Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 13 Oct 2023 08:14
Last Modified: 13 Oct 2023 08:14

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