Design And Implementation Of Data Mining System Based On Dangerous Goods Electronic Waybill

With the rapid development of the national economy,the demand for dangerous goods in production and life is also increasing.Road transportation is the main method of transporting dangerous goods.The State and the Ministry of Transport have implemented a series of measures to improve the safe operation of dangerous goods on road transportation.The application of the electronic waybill management system for dangerous goods road transportation is one of the important measures.The implementation of electronic waybills has greatly improved the scientific and targeted safety management of dangerous goods transportation.But the data of dangerous goods electronic waybill has not yet been systematically mined and analyzed,and the value of the data is difficult to reflect.Based on this,the goal of this article is to design and implement the data mining system for dangerous goods electronic waybills.This article first analyzes the current status of domestic dangerous goods road transportation,and at the same time researches and analyzes the dangerous goods road transportation electronic waybill management system;then it conducts demand analysis of the data mining system and clarifies the function of the system module;finally,adopts B/S structure mode,Flask architecture and My SQL database technology,uses Python as a development tool to achieve the system.This article mainly completes the following work:(1)Conduct a demand analysis of the data mining system based on the electronic waybill of dangerous goods,comb the current situation of road transportation of dangerous goods in China,analyze the current situation and existing problems of the electronic waybill management system of road transportation of dangerous goods,propose construction goals for the system,establish three major data mining function modules include cluster analysis of dangerous goods,demand forecast and statistical analysis visualization.(2)Design the data mining system based on the electronic waybill of dangerous goods.The overall design of the system includes the system design principles,system design schemes,system architecture design and system operation process design.In the algorithm design,the cluster analysis module uses BIRCH.The clustering algorithm performs cluster analysis on the electronic waybill data.The demand forecasting module based on the time series ARIMA model and machine learning XGBoost model and Cat Boost model.Through model evaluation,the three models are linearly combined and the predictive results are output.The statistical analysis and visualized module use tools such as Baidu Map API to perform statistical analysis on dangerous goods transportation behavior and regional dangerous goods.(3)Development and implementation of the data mining system based on electronic waybills of dangerous goods.The system integrates the functions of three modules.Taking the electronic waybill data of road transportation of dangerous goods in Shaanxi Province as the data source,the mining results are visualized in the system interface.The data mining system of dangerous goods electronic waybill can effectively analyze the flow and direction of dangerous goods,which has practical significance for improving the safety management level of dangerous goods road transportation and promoting its information construction process,and can also provide relevant management departments and transportation enterprises with situation analysis and decision support.