Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Jianhong, Chen, Yi, Yang, Shan, Zhong, Xudong, Han, Xu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
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
_version_ 1783430264917065728
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
work_keys_str_mv AT chenjianhong apredictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT chenyi apredictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT yangshan apredictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT zhongxudong apredictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT hanxu apredictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT chenjianhong predictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT chenyi predictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT yangshan predictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT zhongxudong predictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension
AT hanxu predictionmodelonrockburstintensitygradebasedonvariableweightandmatterelementextension