Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier
Compressive strength; Excavation; Forecasting; Underground structures; Boosting classifiers; Case history; Developed model; Early design stages; Key influencing factors; Maximum tangential stress; Project construction; Rockburst intensity; Underground excavation; Uniaxial compressive strength; Adapt...
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2023
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my.uniten.dspace-271922023-05-29T17:40:46Z Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier Ahmad M. Katman H.Y. Al-Mansob R.A. Ahmad F. Safdar M. Alguno A.C. 56531227300 55812804800 55566434500 57204650618 57221085412 7801308675 Compressive strength; Excavation; Forecasting; Underground structures; Boosting classifiers; Case history; Developed model; Early design stages; Key influencing factors; Maximum tangential stress; Project construction; Rockburst intensity; Underground excavation; Uniaxial compressive strength; Adaptive boosting Rockburst phenomenon is the primary cause of many fatalities and accidents during deep underground projects constructions. As a result, its prediction at the early design stages plays a significant role in improving safety. The article describes a newly developed model to predict rockburst intensity grade using Adaptive Boosting (AdaBoost) classifier. A database including 165 rockburst case histories was collected from across the world to achieve a comprehensive representation, in which four key influencing factors such as maximum tangential stress of the excavation boundary, uniaxial compressive strength of rock, tensile rock strength, and elastic energy index were selected as the input variables, and the rockburst intensity grade was selected as the output. The output of the AdaBoost model is evaluated using statistical parameters including accuracy and Cohen's kappa index. The applications for the aforementioned approach for predicting the rockburst intensity grade are compared and discussed. Finally, two real-world applications are used to verify the proposed AdaBoost model. It is found that the prediction results are consistent with the actual conditions of the subsequent construction. � 2022 Mahmood Ahmad et al. Final 2023-05-29T09:40:45Z 2023-05-29T09:40:45Z 2022 Article 10.1155/2022/6156210 2-s2.0-85130610620 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130610620&doi=10.1155%2f2022%2f6156210&partnerID=40&md5=aca48c950c1c0ae550d986161aa26674 https://irepository.uniten.edu.my/handle/123456789/27192 2022 6156210 All Open Access, Gold, Green Hindawi Limited Scopus |
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Compressive strength; Excavation; Forecasting; Underground structures; Boosting classifiers; Case history; Developed model; Early design stages; Key influencing factors; Maximum tangential stress; Project construction; Rockburst intensity; Underground excavation; Uniaxial compressive strength; Adaptive boosting |
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56531227300 |
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56531227300 Ahmad M. Katman H.Y. Al-Mansob R.A. Ahmad F. Safdar M. Alguno A.C. |
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Ahmad M. Katman H.Y. Al-Mansob R.A. Ahmad F. Safdar M. Alguno A.C. |
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Ahmad M. Katman H.Y. Al-Mansob R.A. Ahmad F. Safdar M. Alguno A.C. Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier |
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Ahmad M. |
title |
Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier |
title_short |
Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier |
title_full |
Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier |
title_fullStr |
Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier |
title_full_unstemmed |
Prediction of Rockburst Intensity Grade in Deep Underground Excavation Using Adaptive Boosting Classifier |
title_sort |
prediction of rockburst intensity grade in deep underground excavation using adaptive boosting classifier |
publisher |
Hindawi Limited |
publishDate |
2023 |
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1806428237037830144 |