Stability assessment of hard rock pillars using two intelligent classification techniques: A comparative study
作者： Ebrahim Ghasemi , Hamid Kalhori , Raheb Bagherpour
DOI: 10.1016/J.TUST.2017.05.012
关键词: Data mining 、 Stability assessment 、 Stability (learning theory) 、 Structural engineering 、 Engineering 、 Pillar 、 C4.5 algorithm
摘要: Abstract One of the most challenging safety problems in underground hard rock mines is pillar stability during mining operation. This paper presents an assessment J48 and SVC application for prediction mines. Based on a database compiled from various using these algorithms, two graphs are developed. The performance models indicates that both can predict with acceptable accuracy. In comparison logistic regression model, capability better, but model shows superiority over other models.
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