Enhancing predictions of blast-induced ground vibration in open-pit mines: Comparing swarm-based optimization algorithms to optimize self-organizing neural networks

The objective of this paper is to present a method for predicting blast-induced ground vibration in open-pit mines that is based on the use of self-organizing neural networks (SONIA) and metaheuristic algorithms. In order to improve the accuracy of the SONIA model, several metaheuristic algorithms w...

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Veröffentlicht in:	International journal of coal geology Jg. 275; S. 104294
Hauptverfasser:	Nguyen, Hoang, Bui, Xuan-Nam, Topal, Erkan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.07.2023
Schlagworte:	Applied soft computing Blast-induced ground vibration Metaheuristic optimization algorithm Open-pit coal mine Peak particle velocity Self-organizing neural network FFA DE HPSOGWO PR BNN dh UCS ELM QRNN RVM MRFO NMRA Peak particle velocity BBO MLP CSmj QC ANFIS DOE ML Hh BGAMs BCF SpaSO AI MAPE VOD HKM PSO AO FCM GEP RF HGS JA SONIA ν AutoencoderNN CART ANN RS ABC B D E BI El H SaDE SRH KNN K SVM BO HHO SC Q BSVR R GBM S XGBoost MFO PPV GA Nh Self-organizing neural network GD Tdl Applied soft computing CA CSO GWO ST f ICA Nblast_group Open-pit coal mine WOA CL Pν SCA Sd AGPSO CRANFIS Blast-induced ground vibration PE MARS PF RMR Metaheuristic optimization algorithm HD IM-ANN GFNN
ISSN:	0166-5162
Online-Zugang:	Volltext
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