Research On Application Of Multi-objective Decision And Data Mining In Agriculture And Forestry Fire

Nowadays,forest fires are a serious threat to the environment and human life.The occurrence of fire has the characteristics of suddenness and random.Causing forest fire has three major elements: combustibles,combustion and ignition sources,but also have the appropriate climatic conditions,it is easy to cause a fire,Therefore,the forest fire prediction research is an important prerequisite for the construction of forest fire control,and has a guiding significance to the fire prevention work.This paper mainly uses data mining technology to analyze and excavate forest fire data,analyzed and collates the basic conditions of forest fire in Jiangxi Province,forest fire cases,and forest fire image data,and adopts a data mining platform for exploring the preprocessed data.The paper introduces the status of data mining in forest fire,the general concepts of data mining,the data mining algorithms used,and the development platform tool used.In terms of data collection,first,the basic situation of forest fire in Jiangxi Province from 2006 to 2015 was counted,including the number of fires,fire areas,affected area,direct economic losses,etc.;second,the relationship of the number of fires and climate in Jiangxi Province was statistically analyzed;in the end,the cases of forest fire accidents were collected,and the image data of forest fire were collected and arranged.After pre-processing the data collected,use the MySQL database system to store the data.The data mining model is based on the implementation of the Python OpenCV development platform.It uses association rules,time series,cluster analysis and multi-objective decision-making algorithms to mine the statistics data of forest fire in Jiangxi Province,forest fire cases,and forest fire image data.Detect the intrinsic connections and laws between properties when the fire occurs.The results of the study provide a reference for the application of data mining technology in forest fire,and have certain practical significance in the field of fire prediction research.