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Optimization of mine ventilation network feature graph
A ventilation network feature graph can directly and quantitatively represent the features of a ventilation network. To ensure the stability of airflow in a mine and improve ventilation system analysis, we propose a new algorithm to draw ventilation network feature graphs. The independent path metho...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668600/ https://www.ncbi.nlm.nih.gov/pubmed/33196680 http://dx.doi.org/10.1371/journal.pone.0242011 |
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author | Jia, Jinzhang Li, Bin Ke, Dinglin Wu, Yumo Zhao, Dan Wang, Mingyu |
author_facet | Jia, Jinzhang Li, Bin Ke, Dinglin Wu, Yumo Zhao, Dan Wang, Mingyu |
author_sort | Jia, Jinzhang |
collection | PubMed |
description | A ventilation network feature graph can directly and quantitatively represent the features of a ventilation network. To ensure the stability of airflow in a mine and improve ventilation system analysis, we propose a new algorithm to draw ventilation network feature graphs. The independent path method serves as the algorithm’s main frame, and an improved adaptive genetic algorithm is embedded so that the graph may be drawn better. A mathematical model based on the node adjacency matrix method for unidirectional circuit discrimination is constructed as the drawing algorithm may not be valid in such cases. By modifying the edge-seeking strategy, the improved depth-first search algorithm can be used to determine all of the paths in the ventilation network with unidirectional circuits, and the equivalent transformation method of network topology relations is used to draw the ventilation network feature graph. Through the analysis of the topological relation of a ventilation network, a simplified mathematical model is constructed, and network simplification technology makes the drawing concise and hierarchical. The rapid and intuitive drawing of the ventilation network feature graphs is significant for optimization of the ventilation system and day-to-day management. |
format | Online Article Text |
id | pubmed-7668600 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76686002020-11-19 Optimization of mine ventilation network feature graph Jia, Jinzhang Li, Bin Ke, Dinglin Wu, Yumo Zhao, Dan Wang, Mingyu PLoS One Research Article A ventilation network feature graph can directly and quantitatively represent the features of a ventilation network. To ensure the stability of airflow in a mine and improve ventilation system analysis, we propose a new algorithm to draw ventilation network feature graphs. The independent path method serves as the algorithm’s main frame, and an improved adaptive genetic algorithm is embedded so that the graph may be drawn better. A mathematical model based on the node adjacency matrix method for unidirectional circuit discrimination is constructed as the drawing algorithm may not be valid in such cases. By modifying the edge-seeking strategy, the improved depth-first search algorithm can be used to determine all of the paths in the ventilation network with unidirectional circuits, and the equivalent transformation method of network topology relations is used to draw the ventilation network feature graph. Through the analysis of the topological relation of a ventilation network, a simplified mathematical model is constructed, and network simplification technology makes the drawing concise and hierarchical. The rapid and intuitive drawing of the ventilation network feature graphs is significant for optimization of the ventilation system and day-to-day management. Public Library of Science 2020-11-16 /pmc/articles/PMC7668600/ /pubmed/33196680 http://dx.doi.org/10.1371/journal.pone.0242011 Text en © 2020 Jia 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 Jia, Jinzhang Li, Bin Ke, Dinglin Wu, Yumo Zhao, Dan Wang, Mingyu Optimization of mine ventilation network feature graph |
title | Optimization of mine ventilation network feature graph |
title_full | Optimization of mine ventilation network feature graph |
title_fullStr | Optimization of mine ventilation network feature graph |
title_full_unstemmed | Optimization of mine ventilation network feature graph |
title_short | Optimization of mine ventilation network feature graph |
title_sort | optimization of mine ventilation network feature graph |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668600/ https://www.ncbi.nlm.nih.gov/pubmed/33196680 http://dx.doi.org/10.1371/journal.pone.0242011 |
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