{"title":"Research on the Prediction Framework of Road Traffic Accidents Based on IDWPSO","authors":"Wenbin Bi, Fang Yu","doi":"10.1109/ICVRIS51417.2020.00033","DOIUrl":null,"url":null,"abstract":"In order to overcome the problems of forecasting on an annual basis has little significance for the actual prevention of traffic road accidents In the prediction of the number of road traffic accidents, a new heuristic prediction processing method for small sample data sets based on the IDWPSO prediction framework is proposed. This framework improves the generalization ability of small sample data prediction, avoids local optimization, and ensures the accuracy of road traffic accident prediction. On the basis of the above, comparative simulation experiments with other common traffic accident prediction methods is completed. The simulation results show that the proposed framework can be effectively applied to the direction of information control in the transportation field. Reduce the number of traffic accidents by predicting the number of short-term road traffic accidents.","PeriodicalId":162549,"journal":{"name":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"1 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRIS51417.2020.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In order to overcome the problems of forecasting on an annual basis has little significance for the actual prevention of traffic road accidents In the prediction of the number of road traffic accidents, a new heuristic prediction processing method for small sample data sets based on the IDWPSO prediction framework is proposed. This framework improves the generalization ability of small sample data prediction, avoids local optimization, and ensures the accuracy of road traffic accident prediction. On the basis of the above, comparative simulation experiments with other common traffic accident prediction methods is completed. The simulation results show that the proposed framework can be effectively applied to the direction of information control in the transportation field. Reduce the number of traffic accidents by predicting the number of short-term road traffic accidents.