首页|Research Data from Tsinghua University Update Understanding of Machine Learning (Wildfire risk assessment using deep learning in Guangdong Province,China)
Research Data from Tsinghua University Update Understanding of Machine Learning (Wildfire risk assessment using deep learning in Guangdong Province,China)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in artificial intelligence. According to news reporting from Beijing,People's Repu blic of China,by NewsRx journalists,research stated,"The severe wildfires tha t have ravaged Guangdong province,China,present a significant threat to the lo cal ecosystem,socioeconomics,and public health." Funders for this research include National Natural Science Foundation of China; Guangdong Provincial Department of Science And Technology; Shenzhen Science And Technology Innovation Committee. The news correspondents obtained a quote from the research from Tsinghua Univers ity: "Effective risk assessment is essential for early warning and timely preven tion in wildfire management,thereby mitigating disaster losses. In this study,we compiled a dataset comprising 11,507 historical wildfire incidents in Guangdo ng Province spanning a decade (2011-2021) and developed a deep learning-based mo del to predict the likelihood of wildfire occurrence in the region. In addition to analyzing risk characteristics throughout the year,we also trained separate models for different seasons and analyzed the discrepancies in the contribution of driven factors to wildfire occurrence across seasons. Furthermore,the perfor mance of our deep learning-based model was compared with that of traditional mac hine learning algorithms. The experimental results revealed that: (1) Factors su ch as relative humidity,temperature,NDVI,and precipitation exerted significan t influence on wildfire occurrence. (2) The impact of wildfire driving factors v aried across different seasons."
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