Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration

Accurate prediction of ground vibration caused by blasting has always been a significant issue in the mining industry. Ground vibration caused by blasting is a harmful phenomenon to nearby buildings and should be prevented. In this regard, a new intelligent method for predicting peak particle veloci...

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Vydané v:	Engineering with computers Ročník 38; číslo Suppl 5; s. 4145 - 4162
Hlavní autori:	Qiu, Yingui, Zhou, Jian, Khandelwal, Manoj, Yang, Haitao, Yang, Peixi, Li, Chuanqi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Springer London 01.12.2022 Springer Nature B.V
Predmet:	Algorithms Blasting (explosive) CAE) and Design Calculus of Variations and Optimal Control; Optimization Classical Mechanics Computer Science Computer-Aided Engineering (CAD Control Controllability Dependent variables Explosions Heuristic methods Machine learning Math. Applications in Chemistry Mathematical and Computational Engineering Mining industry Optimization Optimization algorithms Original Article Performance evaluation Root-mean-square errors Systems Theory Vibration Metaheuristic optimization Extreme gradient boosting Blasting Ground vibration PPV Machine learning
ISSN:	0177-0667, 1435-5663
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