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A prediction model on rockburst intensity grade based on variable weight and matter-element extension
Rockburst is a common dynamic disaster in deep underground engineering. To accurately predict rockburst intensity grade, this study proposes a novel rockburst prediction model based on variable weight and matter-element extension theory. In the proposed model, variable weight theory is used to optim...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6594615/ https://www.ncbi.nlm.nih.gov/pubmed/31242202 http://dx.doi.org/10.1371/journal.pone.0218525 |
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author | Chen, Jianhong Chen, Yi Yang, Shan Zhong, Xudong Han, Xu |
author_facet | Chen, Jianhong Chen, Yi Yang, Shan Zhong, Xudong Han, Xu |
author_sort | Chen, Jianhong |
collection | PubMed |
description | Rockburst is a common dynamic disaster in deep underground engineering. To accurately predict rockburst intensity grade, this study proposes a novel rockburst prediction model based on variable weight and matter-element extension theory. In the proposed model, variable weight theory is used to optimize the weights of prediction indexes. Matter-element extension theory and grade variable method are used to calculate the grade variable interval corresponding to the classification standard of rockburst intensity grade. The rockburst intensity grade of Engineering Rock Mass is predicted by rock burst intensity level variable and the interval. Finally, the model is tested by predicting the rockburst intensity grades of worldwide several projects. The prediction results are compared with the actual rockburst intensity grades and the prediction results of other models. The results indicate that, after using variable weight theory and grade variable method, the correct rate of prediction results of matter-element extension model is improved, and the safety of the prediction results is also enhanced. This study provides a new way to predict rock burst in underground engineering. |
format | Online Article Text |
id | pubmed-6594615 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65946152019-07-05 A prediction model on rockburst intensity grade based on variable weight and matter-element extension Chen, Jianhong Chen, Yi Yang, Shan Zhong, Xudong Han, Xu PLoS One Research Article Rockburst is a common dynamic disaster in deep underground engineering. To accurately predict rockburst intensity grade, this study proposes a novel rockburst prediction model based on variable weight and matter-element extension theory. In the proposed model, variable weight theory is used to optimize the weights of prediction indexes. Matter-element extension theory and grade variable method are used to calculate the grade variable interval corresponding to the classification standard of rockburst intensity grade. The rockburst intensity grade of Engineering Rock Mass is predicted by rock burst intensity level variable and the interval. Finally, the model is tested by predicting the rockburst intensity grades of worldwide several projects. The prediction results are compared with the actual rockburst intensity grades and the prediction results of other models. The results indicate that, after using variable weight theory and grade variable method, the correct rate of prediction results of matter-element extension model is improved, and the safety of the prediction results is also enhanced. This study provides a new way to predict rock burst in underground engineering. Public Library of Science 2019-06-26 /pmc/articles/PMC6594615/ /pubmed/31242202 http://dx.doi.org/10.1371/journal.pone.0218525 Text en © 2019 Chen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Chen, Jianhong Chen, Yi Yang, Shan Zhong, Xudong Han, Xu A prediction model on rockburst intensity grade based on variable weight and matter-element extension |
title | A prediction model on rockburst intensity grade based on variable weight and matter-element extension |
title_full | A prediction model on rockburst intensity grade based on variable weight and matter-element extension |
title_fullStr | A prediction model on rockburst intensity grade based on variable weight and matter-element extension |
title_full_unstemmed | A prediction model on rockburst intensity grade based on variable weight and matter-element extension |
title_short | A prediction model on rockburst intensity grade based on variable weight and matter-element extension |
title_sort | prediction model on rockburst intensity grade based on variable weight and matter-element extension |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6594615/ https://www.ncbi.nlm.nih.gov/pubmed/31242202 http://dx.doi.org/10.1371/journal.pone.0218525 |
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