Prediction of Rockburst Based on Multidimensional Connection Cloud Model and Set Pair Analysis
Publication: International Journal of Geomechanics
Volume 20, Issue 1
Abstract
Prediction of rockburst involves numerous random and fuzzy indicators asymmetrically distributed in finite intervals. Herein, a novel multidimensional connection cloud model was introduced to depict uncertainties and distribution characteristics of indicators, and the fuzziness of the classification boundary. In the model, numerical characteristics of the connection cloud model were first determined on the basis of the set pair analysis (SPA) of measured indicators relative to the classification standard. Then a multidimensional connection cloud model was presented to express the interval-valued classification standard. Next, based on the combination weight specified by a distance function, the integrated connection degree for a grade was identified for the sample. Finally, a case study and comparison of the proposed model with the normal cloud model and extensible evaluation method were performed to confirm the validity and reliability of the proposed model. The results show that the proposed model, with a quicker and simpler calculation process than a normal cloud model, can describe the multiple types of uncertainties of interval-valued indicators and overcome the subjectivity when determining numerical characteristics of the cloud model.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request, including data used in the case study and code generated for one of the examples in this paper.
Acknowledgments
Financial support for this study from the National Natural Sciences Foundation of China (Nos. 51579059 and 41172274) and the National Key Research and Development Program of China under Grant Nos. 2016YFC0401303 and 2017YFC1502405 is gratefully acknowledged.
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Published In
International Journal of Geomechanics
Volume 20 • Issue 1 • January 2020
Copyright
©2019 American Society of Civil Engineers.
History
Received: Sep 4, 2018
Accepted: Jun 6, 2019
Published online: Nov 13, 2019
Published in print: Jan 1, 2020
Discussion open until: Apr 13, 2020
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