Cargando…
Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks
This paper focuses on the application of higher-order and multilayer networks in identifying critical causes and relationships contributing to hazardous materials transportation accidents. There were 792 accidents of hazardous materials transportation that occurred on the road from 2017 to 2021 whic...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378565/ https://www.ncbi.nlm.nih.gov/pubmed/37509983 http://dx.doi.org/10.3390/e25071036 |
_version_ | 1785079798899408896 |
---|---|
author | Ren, Cuiping Chen, Bianbian Xie, Fengjie |
author_facet | Ren, Cuiping Chen, Bianbian Xie, Fengjie |
author_sort | Ren, Cuiping |
collection | PubMed |
description | This paper focuses on the application of higher-order and multilayer networks in identifying critical causes and relationships contributing to hazardous materials transportation accidents. There were 792 accidents of hazardous materials transportation that occurred on the road from 2017 to 2021 which have been investigated. By considering time sequence and dependency of causes, the hazardous materials transportation accidents causation network (HMTACN) was described using the higher-order model. To investigate the structure of HMTACN such as the importance of causes and links, HMTACN was divided into three layers using the weighted k-core decomposition: the core layer, the bridge layer and the peripheral layer. Then causes and links were analyzed in detail. It was found that the core layer was tightly connected and supported most of the causal flows of HMTACN. The results showed that causes should be given hierarchical attention. This study provides an innovative method to analyze complicated accidents, which can be used in identifying major causes and links. And this paper brings new ideas about safety network study and extends the applications of complex network theory. |
format | Online Article Text |
id | pubmed-10378565 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103785652023-07-29 Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks Ren, Cuiping Chen, Bianbian Xie, Fengjie Entropy (Basel) Article This paper focuses on the application of higher-order and multilayer networks in identifying critical causes and relationships contributing to hazardous materials transportation accidents. There were 792 accidents of hazardous materials transportation that occurred on the road from 2017 to 2021 which have been investigated. By considering time sequence and dependency of causes, the hazardous materials transportation accidents causation network (HMTACN) was described using the higher-order model. To investigate the structure of HMTACN such as the importance of causes and links, HMTACN was divided into three layers using the weighted k-core decomposition: the core layer, the bridge layer and the peripheral layer. Then causes and links were analyzed in detail. It was found that the core layer was tightly connected and supported most of the causal flows of HMTACN. The results showed that causes should be given hierarchical attention. This study provides an innovative method to analyze complicated accidents, which can be used in identifying major causes and links. And this paper brings new ideas about safety network study and extends the applications of complex network theory. MDPI 2023-07-10 /pmc/articles/PMC10378565/ /pubmed/37509983 http://dx.doi.org/10.3390/e25071036 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ren, Cuiping Chen, Bianbian Xie, Fengjie Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks |
title | Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks |
title_full | Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks |
title_fullStr | Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks |
title_full_unstemmed | Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks |
title_short | Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks |
title_sort | identifying key factors of hazardous materials transportation accidents based on higher-order and multilayer networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378565/ https://www.ncbi.nlm.nih.gov/pubmed/37509983 http://dx.doi.org/10.3390/e25071036 |
work_keys_str_mv | AT rencuiping identifyingkeyfactorsofhazardousmaterialstransportationaccidentsbasedonhigherorderandmultilayernetworks AT chenbianbian identifyingkeyfactorsofhazardousmaterialstransportationaccidentsbasedonhigherorderandmultilayernetworks AT xiefengjie identifyingkeyfactorsofhazardousmaterialstransportationaccidentsbasedonhigherorderandmultilayernetworks |