首页|Studies from China University of Mining and Technology Update Current Data on Machine Learning (Fire Source Determination Method for Underground Commercial Streets Based on Perception Data and Machine Learning)
Studies from China University of Mining and Technology Update Current Data on Machine Learning (Fire Source Determination Method for Underground Commercial Streets Based on Perception Data and Machine Learning)
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Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Shenzhen, People’s Republic of China, by NewsRx editors, research stated, “Determining fire source in underground commercial street fires is critical for fire analysis.” Funders for this research include Jiangsu Provincial Department of Science And Technology; Shenzhen City General Program; Science And Technology Plan Project of The Fire And Rescue Administration of The Ministry of Emergency Management. Our news reporters obtained a quote from the research from China University of Mining and Technology: “This paper proposes a method based on temperature and machine learning to determine information about fire source in underground commercial street fires. Data was obtained through consolidated fire and smoke transport (CFAST) software, and a fire database was established based on the sampling to ascertain fire scenarios. Temperature time series were chosen for feature processing, and three machine learning models for fire source determination were established: decision tree, random forest, and LightGBM. The results indicated that the trained models can determine fire source information based on processed features, achieving a precision exceeding 95%.”
China University of Mining and TechnologyShenzhenPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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