| Under the background of advocating the concept of environmental protection and implementing the green travel action plan,the demand for public transportation has been increased all over the country,and the safety of public transportation has also received more and more attention.As a kind of public transportation,bus is an important tool for urban residents to travel and bears the responsibility of carrying urban residents.However,compared with subway,light rail and other rail transit,buses and other vehicles run on the ground together and are often greatly affected by road traffic conditions,and the influencing factors of accidents are more complex.In addition,compared with general motor vehicles,buses have a fixed driving route,a fixed operating time,a large number of passengers,and a special bus lane,which is different from the influence factors of general motor vehicle accidents.External factors are the important causes of bus accidents,so this paper studies the external causes of bus accidents,and puts forward corresponding measures according to the research results,in order to improve the traffic safety level of buses in China.The main work includes the following aspects.(1)The current situation of bus accidents at home and abroad can be obtained by consulting the data.At the same time,the external influencing factors of bus accidents are identified by using literature induction method.(2)An optimization algorithm based on Apriori algorithm which is suitable for multi-dimensional data mining is applied to mine bus accident data.At the same time,according to the mining purpose of bus accident data,the corresponding subjective constraint conditions are put forward to guide the multi-dimensional association rule mining and further improve the mining efficiency.(3)The concrete flow and method of mining multidimensional association rules for bus accidents are put forward.Firstly,data preprocessing is carried out.Secondly,SQL Server is used to build multi-dimensional multi-layer data model and realize multi-dimensional data storage.Then,an optimized Apriori algorithm is written using C# language.Finally,parameter values are set and subjective constraints are added.Visual Studio software is used to develop mining tools to realize the mining of multi-dimensional association rules for bus accidents.(4)The concrete flow and method of mining multidimensional association rules for bus accidents are put forward.Firstly,data preprocessing is carried out.Secondly,SQL Server is used to build multi-dimensional multi-layer data model and realize multi-dimensional data storage.Then,an optimized Apriori algorithm is written using C# language.Finally,parameter values are set and subjective constraints are added.Visual Studio software is used to develop mining tools to realize the mining of multi-dimensional association rules for bus accidents. |
