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Geological Engineering: Proceedings of the 1st International Conference (ICGE 2007)

Editor
Baosong Ma
Baosong Ma
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ISBN:
9780791802922
No. of Pages:
1760
Publisher:
ASME Press
Publication date:
2009

Rockburst is a geological disaster occurred usually in deep mines. Because of poor understanding of the mechanism and influence factors of rockbust, it is very difficult to give accurate prediction using conventional methods. A new model based on Gaussian process (GP), which is a probabilistic kernel machine leaning and has become a power tool for solving highly nonlinear problems, therefore, is proposed. At first, case histories of rockburst occurrence with the real records of rockburst intensity and influence factors of rockbust are collected and are taken as prior knowledge to be learned by GP binary classification machine learning. Maximum tangential...

Abstract
Introduction
GP Binary Classification
GP Model for Rockburst Prediction
Case Study
Conclusion
Acknowledgment
References
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