A Connection Cloud-Evidence Theory Coupling Model for Prediction of Rockburst Intensity

WANG Mingwu; DONG Hao; YE Hui; ZHOU Tianlong; JIN Juliang

doi:10.21656/1000-0887.380286

Volume 39 Issue 9

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Article Navigation > Applied Mathematics and Mechanics > 2018 > 39(9): 1021-1029

WANG Mingwu, DONG Hao, YE Hui, ZHOU Tianlong, JIN Juliang. A Connection Cloud-Evidence Theory Coupling Model for Prediction of Rockburst Intensity[J]. Applied Mathematics and Mechanics, 2018, 39(9): 1021-1029. doi: 10.21656/1000-0887.380286

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A Connection Cloud-Evidence Theory Coupling Model for Prediction of Rockburst Intensity

doi: 10.21656/1000-0887.380286

School of Civil and Hydraulic Engineering, Hefei University of Technology, Hefei 230009, P.R.China

Funds: The National Key R&D Plan(2016YFC0401303)； The National Natural Science Foundation of China（41172274； 51579059）

Received Date: 2017-11-13
Rev Recd Date: 2018-01-31
Publish Date: 2018-09-15

Abstract

Abstract

Rockburst mechanism is a complex problem involving various uncertain factors. Although the cloud model can deal with the randomness and fuzziness of indicators for prediction of rockburst intensity, it cannot simulate the state of evaluation indicators in a finite distribution interval and address the distortion of data fusion. Herein, a connection cloud-evidence theory coupling model was built to remedy these defects. In this model, evaluation indicators were firstly expressed quantitatively by connection numbers. Then the evaluation matrix was constructed with the connection cloud model and the basic probability assignment based on the evidence theory was obtained. Finally, with the combination weight obtained from a distance function, classification of the rockburst intensity was determined according to the mean evidence value. The case study and comparison with other methods show that, the proposed model is effective and feasible for the prediction of rockburst intensity. It can overcome the shortcomings of the normal cloud model and the evidence theory, making a novel method for comprehensive prediction of rockburst intensity.
- connection cloud,
- evidence theory,
- rockburst,
- prediction,
- combination weight

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References(17)

References

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