Research on Characteristic Mining of Fire Risk Data in Typical Areas
With the technological development of the IoT and big data,the prevention and control of urban fire risk in China becomes increasingly intelligent.A large amount of multi-dimensional and dynamic data has been accumulated in urban social governance and daily firefighting work,which provides the basis for more valuable data mining.In this manuscript,the data which obtained from fire department business platform,government official website etc.were comprehensively analyzed and stud-ied using data mining method.Firstly,a descriptive statistical analysis of databases was made by the visual display.Secondly,PCA(principal component analysis)and Decision Tree models were used to study the relationship between fire risk and environ-mental factors data,and the dimension reduction analysis model was built.Finally,by analyzing the data rule of the model out-put,the characteristic trend among the attributes of the data set was studied,and the valued suggestions were introduced for the construction and application of fire protection big data.
fire riskdata analysisdata miningprincipal component analysisdecision tree
NETL
NSTL
万方数据
