The Prediction And Visualization Realization Of Traffic Accident Based On Optimal Weighted Combined Model

The current traffic accidents situation in China was so serious that adopting effective measures to drop the accident occurrence rate became an urgent problem need to be solved. According to the achievements of control traffic accidents in developed countries, based on historical accidents data establishing mathematical model, to predict future traffic accident mortality effectively could provide guide for traffic administrative departs to formulate scientific management, which is a feasible method of reducing traffic accidents. However, the current mathematical model just reflected partial characteristic of origin data, more importantly, the prediction model was single. To integrate single model into combined model in current research was infrequent while visualization of traffic accident was sparser.Based on historical data of traffic accident, the mathematical model was established to predict future traffic accident number. According to the different traits, the model was divided into weighted combined model for whole country and grey model for every province. The prediction process was performed by MATLAB platform and error estimating index was applied to evaluate the accuracy of mathematical models. After acquiring the prediction results, the visualization of these data was displayed in this paper. The visualization was fulfilled base on Echarts system including dynamic time axial show and static exhibition, and the visualization contained the whole country data and every province.The results demonstrated that the mathematical model constructed in this paper has excellent accuracy. The accomplishment of visualization could exhibit numerous prediction data visually, which provided foundation for analyzing prediction data systemically and extensively. Besides, the investigation in this paper displayed brief and useful traffic accident prediction visualization information, which could provide reference for both traffic accident prediction and formulating of relevant policy. These results was not only beneficial to improve the security of traffic transportation, but also was of long-term social and economic significance.