An Improved Stacking Model for Forest Fire Susceptibility Prediction in Chongqing City, China-Reference-Cited by-同舟云学术

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An Improved Stacking Model for Forest Fire Susceptibility Prediction in Chongqing City, China

Published:2023-08-28 Issue: Volume:17 Page:1-6
ISSN:
Container-title:2023 IEEE Smart World Congress (SWC)
language:
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Author:

Li Yanzhi¹,Li Keqiu²,Wang Kaifeng³,Li Guohui⁴,Wang Zumin³

Affiliation:

1. Tianjin University Tianjin Fire Science and Technology Research Institute of MEM,College of Intelligence and Computing,Tianjin,China

2. Tianjin University,College of Intelligence and Computing,Tianjin,China

3. Dalian University,College of Information Engineering,Dalian,China

4. Research Institute of MEM,Tianjin Fire Science and Technology,Tianjin,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10447020/10448518/10449165.pdf?arnumber=10449165

Reference23 articles.

1. Attribution of the Influence of Human‐Induced Climate Change on an Extreme Fire Season

2. The Impact of Precipitation Regimes on Forest Fires in Yunnan Province, Southwest China

3. Multi-criteria decision analysis for forest fire risk assessment by coupling AHP and GIS: method and case study

4. Modeling susceptibility to forest fires in the Central Corridor of the Atlantic Forest using the frequency ratio method

5. Modeling the spatial variation of the explanatory factors of human-caused wildfires in Spain using geographically weighted logistic regression

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Innovative Investigation on Predicting Forest Fire Using Machine Learning Approach;Advances in Computational Intelligence and Robotics;2024-06-28

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