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。
This article used genetic algorithm to optimize the neural network method （ GA - BP neural network } based on the Multi - level Grey Evaluation method, and established the identification model of traffic accident prone sections in Uru- mqi city roads. The predicted values of GA - BP neural network were in good agreement with the multi - level grey evalua- tion results, which verified the feasibility of the identification of roads traffic accident prone sections. GA - BP neural net- work 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.
出处
《科技管理研究》
CSSCI
北大核心
2015年第15期222-226,共5页
Science and Technology Management Research
基金
国家自然科学青年基金项目"浮动车数据与固定检测数据融合的旅行时间估计误差机理研究"(51108398)
关键词
道路交通事故
多发路段鉴别
遗传算法
神经网络
多层次灰色评价
road traffic accident
traffic accident identification
GA algorithms
neural network
multi - level grey evalu- ation
