Research on the Prediction Framework of Road Traffic Accidents Based on IDWPSO

Wenbin Bi, Fang Yu
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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.
基于IDWPSO的道路交通事故预测框架研究
为了克服每年一次的预测对实际预防交通事故意义不大的问题,在道路交通事故数量的预测中,提出了一种基于IDWPSO预测框架的小样本数据集启发式预测处理方法。该框架提高了小样本数据预测的泛化能力,避免了局部优化,保证了道路交通事故预测的准确性。在此基础上,完成了与其他常用交通事故预测方法的对比仿真实验。仿真结果表明,该框架可以有效地应用于交通领域的信息方向控制。通过预测短期道路交通事故的数量,减少交通事故的数量。
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