Research On Modeling And Evaluation Mechanism Of Automobile Safety Inspection System

With the continuous progress of science and technology and the continuous development of economy,cars are playing an increasingly important role in people's daily life.Traffic is becoming more and more complex,causing traffic accidents to increase year by year.Among the many factors that cause traffic collision accidents,it is mainly divided into two aspects: external environmental factors and auto factors.In these factors,what are the main factors can be analyzed by the rough set theory,it is necessary to achieve it through the rough set theory.Therefore,the research on the modeling and evaluation mechanism of automobile safety detection system has a very important social value.Automobile safety can be divided into active safety and passive safety for various factors affecting automobilr safety.On the basis of a large number of literature analysis at home and abroad,the modeling of automobile safety inspection system is studied in the thesis.Firstly,in the automotive passive safety,aiming at the fault of automobile engine,a calculation method of improved SOM clustering continuous attribute discretization is proposed,rough set algorithm can only make up for the shortcomings of discrete data processing made.The SOM method is used in this method to make the discretization of the target data,and the optimal weights of the initial cluster center was obtained,and then the two clustering on the initial output obtained by use of K-means clustering algorithm and the result of the SOM method,get the number of samples,and the samples included in the arrangement and belongs to cluster,to obtain the final discretization results.Secondly,the rough set theory is used to model it,and the neighborhood rough set theory is used to deal with the same set of data.Lastly,on the basis of the traditional rough set theory,the rough intensivism based on particle swarm optimization algorithm is proposed,then the reduction results of the three algorithms are compared,and the MATLAB is used for simulation.The results show that the rough set attribute reduction can be achieved based on the purpose of the automobile safety detection.The reliability of the attribute reduction algorithm based on the particle swarm optimization algorithm is proved again by the modeling of the active safety of the automobile.Through the analysis of vehicle safety inspection system modeling and evaluation mechanism,the accuracy of vehicle fault detection can be improved,vehicle collision probability will be reduced,and the safety and stability of vehicle will be ensured.