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Engineering with Computers
Erschienen in: Engineering with Computers 1/2020

09.01.2019 | Original Article

Evaluation of rockburst occurrence and intensity in underground structures using decision tree approach

verfasst von: Ebrahim Ghasemi, Hasan Gholizadeh, Amoussou Coffi Adoko

Erschienen in: Engineering with Computers | Ausgabe 1/2020

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Abstract

Based on reported statistics, rockburst phenomenon is the main cause of many casualties and accidents occurred during the construction of deep underground structures. Therefore, its prediction in initial stages of design has a remarkable role on enhancement of safety. In this paper, two models have been developed for rockburst evaluation using the C5.0 decision tree classifier. The first model has been applied for prediction of rockburst occurrence and the second model for prediction of rockburst intensity. These models have been developed based on a database including 174 rockburst case histories. In both models, stress coefficient, rock brittleness coefficient, and the elastic strain energy index are the predictive variables. These models are easy to use and do not require extensive knowledge. Based on decision rules derived from these models, the rockburst occurrence and intensity can be evaluated easily. The results revealed that the proposed approach is a useful and robust technique for long-term prediction of rockburst.
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Metadaten
Titel
Evaluation of rockburst occurrence and intensity in underground structures using decision tree approach
verfasst von
Ebrahim Ghasemi
Hasan Gholizadeh
Amoussou Coffi Adoko
Publikationsdatum
09.01.2019
Verlag
Springer London
Erschienen in
Engineering with Computers / Ausgabe 1/2020
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-018-00695-9

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