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Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China

Aiming at the low mining rate in mines, Xingelao, Dabianyao, and Dongliang Coal Mines in Shenmu Mining Area, Shaanxi Province, China were taken as research objects. Based on this, this study constructed an evaluation index system for the mining capacity of the mines from the perspectives of geologic...

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Autores principales: Chen, Haoyi, Cheng, Zhiheng, Kong, Dezhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358539/
https://www.ncbi.nlm.nih.gov/pubmed/34605331
http://dx.doi.org/10.1177/00368504211044032
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author Chen, Haoyi
Cheng, Zhiheng
Kong, Dezhong
author_facet Chen, Haoyi
Cheng, Zhiheng
Kong, Dezhong
author_sort Chen, Haoyi
collection PubMed
description Aiming at the low mining rate in mines, Xingelao, Dabianyao, and Dongliang Coal Mines in Shenmu Mining Area, Shaanxi Province, China were taken as research objects. Based on this, this study constructed an evaluation index system for the mining capacity of the mines from the perspectives of geological factors, mechanical equipment, humans, and mining design. Moreover, the factors influencing the mining capacity of the mines were evaluated using a combination weighting approach based on an improved analytic hierarchy process and an entropy weight method. A standard cloud was generated based on the mapping standards of each index and a comprehensive cloud was obtained according to comprehensive weight and a backward cloud algorithm. Finally, by combining the comprehensive cloud with local and overall scores of the mines, the mining capacities of the mines were evaluated. The research results demonstrate that the key factor restricting the mining capacity of the mines is the geological environment and five major third-grade indexes affecting mining capacity are igneous rock intrusion, collapse column, scouring zone of the ancient river bed, mechanization level and coal pillar width. In addition, the corresponding suggestions and measures were put forward according to the main factors influencing the mining rate of the mines. In accordance with the weights and scores of each index, the overall scores of the mines were calculated. Dongliang, Dabianyao, and Xingelao Coal Mines were ranked in order based on scores. The research results provide a theoretical basis for improving the mining capacity of the mines under similar geological conditions.
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spelling pubmed-103585392023-08-09 Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China Chen, Haoyi Cheng, Zhiheng Kong, Dezhong Sci Prog Original Manuscript Aiming at the low mining rate in mines, Xingelao, Dabianyao, and Dongliang Coal Mines in Shenmu Mining Area, Shaanxi Province, China were taken as research objects. Based on this, this study constructed an evaluation index system for the mining capacity of the mines from the perspectives of geological factors, mechanical equipment, humans, and mining design. Moreover, the factors influencing the mining capacity of the mines were evaluated using a combination weighting approach based on an improved analytic hierarchy process and an entropy weight method. A standard cloud was generated based on the mapping standards of each index and a comprehensive cloud was obtained according to comprehensive weight and a backward cloud algorithm. Finally, by combining the comprehensive cloud with local and overall scores of the mines, the mining capacities of the mines were evaluated. The research results demonstrate that the key factor restricting the mining capacity of the mines is the geological environment and five major third-grade indexes affecting mining capacity are igneous rock intrusion, collapse column, scouring zone of the ancient river bed, mechanization level and coal pillar width. In addition, the corresponding suggestions and measures were put forward according to the main factors influencing the mining rate of the mines. In accordance with the weights and scores of each index, the overall scores of the mines were calculated. Dongliang, Dabianyao, and Xingelao Coal Mines were ranked in order based on scores. The research results provide a theoretical basis for improving the mining capacity of the mines under similar geological conditions. SAGE Publications 2021-10-04 /pmc/articles/PMC10358539/ /pubmed/34605331 http://dx.doi.org/10.1177/00368504211044032 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Manuscript
Chen, Haoyi
Cheng, Zhiheng
Kong, Dezhong
Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China
title Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China
title_full Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China
title_fullStr Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China
title_full_unstemmed Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China
title_short Evaluation of mining capacity of mines using the combination weighting approach: A case study in Shenmu Mining Area in Shaanxi Province, China
title_sort evaluation of mining capacity of mines using the combination weighting approach: a case study in shenmu mining area in shaanxi province, china
topic Original Manuscript
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358539/
https://www.ncbi.nlm.nih.gov/pubmed/34605331
http://dx.doi.org/10.1177/00368504211044032
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