Prediction of rockburst risk in underground projects developing a neuro-bee intelligent system
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Title
Prediction of rockburst risk in underground projects developing a neuro-bee intelligent system
Authors
Keywords
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Journal
Bulletin of Engineering Geology and the Environment
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-05-16
DOI
10.1007/s10064-020-01788-w
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- (2015) Danial Jahed Armaghani et al. Arabian Journal of Geosciences
- Knowledge-based and data-driven fuzzy modeling for rockburst prediction
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