Grid Search Optimised Artificial Neural Network for Open Stope Stability Prediction. Issue 8 (14th September 2021)

• Record Type: Journal Article
• Authors: Erdogan Erten, Gamze; Bozkurt Keser, Sinem; Yavuz, Mahmut
• Is Part Of: International journal of mining, reclamation and environment. Volume 35:Issue 8(2021)
• Page Start: 600
• Page End: 617
• Publication Date: 2021-09-14
• Subjects: Stope stability -- machine learning -- artificial neural network -- grid search; Mining engineering -- Periodicals; Mineral industries -- Environmental aspects -- Periodicals; Abandoned mined lands reclamation -- Periodicals; 622.292
• DOI: 10.1080/17480930.2021.1899404
• Languages: English
• ISSNs: 1748-0930

Abstract

ABSTRACT: The assessment of the stope stability is of great importance in the underground mine design process. The instability of stopes leads to serious economic and safety problems in mining operations. This paper aims to assist in the prediction of stope stability by making use of machine learning algorithms. For this purpose, a hybrid grid search-based Artificial Neural Network method is proposed. In the experiments, a total of 215 stope cases which have been collected from six underground mining operations located across Australia are used to prove the validity of the proposed method. Then, the performance of the proposed method is compared with k-nearest neighbour (kNN), naive Bayes (NB), support vector machine (SVM), decision tree (DT) and the stability graph method. Furthermore, several performance measures, such as accuracy, precision, specificity, recall, f-measure, and g-mean are considered during the performance comparison of the methods. The accuracy values are obtained as 91.63%, 81.86%, 77.21%, 76.74%, 73.95%, and 69.77% with the proposed hybrid grid search-based ANN method, SVM, DT, NB, kNN, and the stability graph method, respectively. The empirical results from the experiments indicated that the proposed hybrid approach outperformed the other aforementioned methods, which confirms that the proposed method is a useful tool to predict stope stability.