RB F 神经网络在公交行程时间预测中的应用
RB F 신경망락재공교행정시간예측중적응용
Bus Travel Time Prediction with Radial Basis Function Neural Network
  • 万方数据
    交通科技与经济 교통과기여경제
    Technology & Economy in Areas of Communications
    2015年 2期 69-73 ,共5页

    肖汶谦%陆百川%郭桂林%张海

    초문겸%륙백천%곽계림%장해

    公共交通%行程时间%预测%RB F神经网络 公共交通%行程時間%預測%RB F神經網絡
    공공교통%행정시간%예측%RB F신경망락
    public transportation%travel time%prediction%RBF neural network
    为提高公交行程时间预测结果准确度、减少预测过程花费时间，提出基于RB F神经网络公交行程时间预测模型。综合分析公交车辆行程时间动静态影响因素后，将网络变量输入模型对行程时间进行预测，以重庆市462公交线路为例，对模型进行验证，对比BP网络预测结果，表明RBF模型在速度和精确度上优于BP网络，具有一定实际应用价值。
    위제고공교행정시간예측결과준학도、감소예측과정화비시간，제출기우RB F신경망락공교행정시간예측모형。종합분석공교차량행정시간동정태영향인소후，장망락변량수입모형대행정시간진행예측，이중경시462공교선로위례，대모형진행험증，대비BP망락예측결과，표명RBF모형재속도화정학도상우우BP망락，구유일정실제응용개치。
    In order to improve the accuracy of bus travel time prediction and reduce the prediction time ,a prediction model of bus travel time was puts forward based on RBF neural network ,analyzing the influence factors of bus travel time comprehensively ,then use the RBF neural network model to predict the travel time .Taking 462 bus line as an example in Chongqing City to verify the model ,contracting with prediction results of BP network and indicating that the RBF model is better than BP network in the speed and accuracy .And the model has practical application value .
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