Rockburst Intensity Classification Prediction Based on Multi-Model Ensemble Learning Algorithms

Rockburst is a common and huge hazard in underground engineering, and the scientific prediction of rockburst disasters can reduce the risks caused by rockburst. At present, developing an accurate and reliable rockburst risk prediction model remains a great challenge due to the difficulty of integrat...

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Vydané v:	Mathematics (Basel) Ročník 11; číslo 4; s. 838
Hlavní autori:	Wang, Jiachuang, Ma, Haoji, Yan, Xianhang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.02.2023
Predmet:	Algorithms Analysis Classification Combinatorial analysis Data mining Decision theory Engineering Ensemble learning Food science fusion strategy Grid method Integrated approach Machine learning Methods Neural networks Optimization Performance enhancement Performance prediction Prediction models Risk rockburst prediction Rockbursts SMOTE data oversampling Stacking stacking integration algorithm Support vector machines voting integration algorithm China
ISSN:	2227-7390, 2227-7390
On-line prístup:	Získať plný text
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