Fire Risk Assessment and Warning Based on Hierarchical Density-Based Spatial Clustering Algorithm and Grey Relational Analysis

Understanding the spatial and temporal distribution patterns of fire is of ecological, social and economic importance. The purpose of this study is to examine the spatial distribution of high fire risk using machine learning algorithms and early warning weather in high-risk areas. Take the satellite...

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Vydáno v:	Mathematical problems in engineering Ročník 2022; s. 1 - 8
Hlavní autoři:	Huang, Junbo, Xu, Zhen, Yang, Feng, Zhang, Wenjuan, Cai, Shuyu, Luo, Jiqiang, Xie, Guobo, Li, Tianyu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Hindawi 13.04.2022 John Wiley & Sons, Inc
Témata:	Algorithms Cluster analysis Clustering Correlation analysis Data mining Density Distribution patterns Emergency warning programs Fire point Fire prevention Forest & brush fires Genetic algorithms Humidity Machine learning Mathematical problems Precipitation Remote sensing Risk assessment Satellites Seasons Spatial distribution Temporal distribution Transmission lines Weather Wind speed Zoning China Yunnan China
ISSN:	1024-123X, 1563-5147
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Abstract	Understanding the spatial and temporal distribution patterns of fire is of ecological, social and economic importance. The purpose of this study is to examine the spatial distribution of high fire risk using machine learning algorithms and early warning weather in high-risk areas. Take the satellite monitored fire point data in Yunnan Province during 2015–2019 as an example. The spatial distribution law of high-density parts is found using hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm, and the correlation degree analysis of high-density fire areas based on clustering and annual mean meteorological factors is carried out using grey correlation analysis (GCA) method. Results illustrates that within five years, fires frequently occurred in the seven regions of Wenshan Zhuang and Miao Autonomous Prefecture, Honghe Hani and Yi Autonomous Prefecture, Lijiang City, Pu’er City, and Xishuangbanna Dai Autonomous Prefecture. Among them, the fire in Lijiang had the greatest relationship with precipitation, Pu’er and Xishuangbanna had the greatest correlation with temperature, and Honghe Hani and Wenshan Zhuang were most affected by wind speed. This article acclaims fire prevention in key periods, key areas, key weather and reinforces the protection of transmission lines in the risk area.
AbstractList	Understanding the spatial and temporal distribution patterns of fire is of ecological, social and economic importance. The purpose of this study is to examine the spatial distribution of high fire risk using machine learning algorithms and early warning weather in high-risk areas. Take the satellite monitored fire point data in Yunnan Province during 2015–2019 as an example. The spatial distribution law of high-density parts is found using hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm, and the correlation degree analysis of high-density fire areas based on clustering and annual mean meteorological factors is carried out using grey correlation analysis (GCA) method. Results illustrates that within five years, fires frequently occurred in the seven regions of Wenshan Zhuang and Miao Autonomous Prefecture, Honghe Hani and Yi Autonomous Prefecture, Lijiang City, Pu’er City, and Xishuangbanna Dai Autonomous Prefecture. Among them, the fire in Lijiang had the greatest relationship with precipitation, Pu’er and Xishuangbanna had the greatest correlation with temperature, and Honghe Hani and Wenshan Zhuang were most affected by wind speed. This article acclaims fire prevention in key periods, key areas, key weather and reinforces the protection of transmission lines in the risk area.
Author	Xie, Guobo Huang, Junbo Li, Tianyu Xu, Zhen Zhang, Wenjuan Yang, Feng Luo, Jiqiang Cai, Shuyu
Author_xml	– sequence: 1 givenname: Junbo surname: Huang fullname: Huang, Junbo organization: Transmission Branch of Yunnan Power Grid Co., Ltd.Kunming, 650000China – sequence: 2 givenname: Zhen surname: Xu fullname: Xu, Zhen organization: Transmission Branch of Yunnan Power Grid Co., Ltd.Kunming, 650000China – sequence: 3 givenname: Feng surname: Yang fullname: Yang, Feng organization: Transmission Branch of Yunnan Power Grid Co., Ltd.Kunming, 650000China – sequence: 4 givenname: Wenjuan surname: Zhang fullname: Zhang, Wenjuan organization: Transmission Branch of Yunnan Power Grid Co., Ltd.Kunming, 650000China – sequence: 5 givenname: Shuyu surname: Cai fullname: Cai, Shuyu organization: Transmission Branch of Yunnan Power Grid Co., Ltd.Kunming, 650000China – sequence: 6 givenname: Jiqiang orcidid: 0000-0001-6769-6661 surname: Luo fullname: Luo, Jiqiang organization: China Academy of Space Technology Institute of Spacecraft System EngineeringBeijing 100094China – sequence: 7 givenname: Guobo surname: Xie fullname: Xie, Guobo organization: School of Computer ScienceGuangdong University of TechnologyGuangzhouChinagist.ac.kr – sequence: 8 givenname: Tianyu orcidid: 0000-0001-6566-7090 surname: Li fullname: Li, Tianyu organization: School of Computer ScienceGuangdong University of TechnologyGuangzhouChinagist.ac.kr
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Copyright	Copyright © 2022 Junbo Huang et al. Copyright © 2022 Junbo Huang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms	Algorithms Cluster analysis Clustering Correlation analysis Data mining Density Distribution patterns Emergency warning programs Fire point Fire prevention Forest & brush fires Genetic algorithms Humidity Machine learning Mathematical problems Precipitation Remote sensing Risk assessment Satellites Seasons Spatial distribution Temporal distribution Transmission lines Weather Wind speed Zoning
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