GA-BP神经网络和多层次灰色评价法在乌鲁木齐市道路交通事故多发路段鉴别中的应用

Application of GA-BP-NN and Multi-level Grey Evaluation in the identification of traffic accident prone sections in Urumqi city roads

摘要:

在应用多层次灰色评价方法的基础上,采用遗传算法优化的神经网络方法(GA-BP神经网络),构建了乌鲁木齐市道路交通事故多发路段的鉴别模型。GA-BP神经网络模型预测值与多层次灰色评价结果吻合良好,验证了GA-BP神经网络方法鉴别道路交通事故多发路段的可行性。GA-BP神经网络有着较高的收敛速度和预测精度,为乌鲁木齐市道路交通事故多发路段鉴别提供了一种新的思路与方法。

Abstract:

This article used genetic algorithm to optimize the neural network method (GA-BP neural network) based on the Multi-level Grey Evaluation method,established the identification model of traffic accident prone sections in Urumqi city roads. The predicted values of GA-BP neural network were in good agreement with the multi-level grey evaluation results,which verified the feasibility of the identification of roads traffic accident prone sections.GA-BP neural network has a higher convergence speed and prediction accuracy,providing a new idea and method for identification of traffic accident prone sections of roads in Urumqi city.