CAJ | 학술논문

对轨道不平顺的发展趋势进行有效预测,可以提高铁路线路养护的维修效率,保障行车安全。根据轨道不平顺的发展特性,提出一种基于非等时距加权灰色理论和神经网络法的组合预测方法。该方法通过构建非等时距加权灰色预测模型,将原始TQI序列的平均值作为累加序列初值,将连续累积函数的积分面积作为背景值,对累加序列进行加权处理,较好地反映了时间序列对轨道不平顺预测结果的贡献。在此基础上,引入 BP 神经网络模型对TQI预测的残差序列进行修正,较好地克服了单一模型预测精度偏低的不足。分别对沪昆线上行两段线路的轨道不平顺进行预测,结果表明该预测方法相对误差平均值分别为2.76%和2.08%,预测结果的后验差比值分别为0.121和0.151,精度等级达到1级。
대궤도불평순적발전추세진행유효예측,가이제고철로선로양호적유수효솔,보장행차안전。근거궤도불평순적발전특성,제출일충기우비등시거가권회색이론화신경망락법적조합예측방법。해방법통과구건비등시거가권회색예측모형,장원시TQI서렬적평균치작위루가서렬초치,장련속루적함수적적분면적작위배경치,대루가서렬진행가권처리,교호지반영료시간서렬대궤도불평순예측결과적공헌。재차기출상,인입 BP 신경망락모형대TQI예측적잔차서렬진행수정,교호지극복료단일모형예측정도편저적불족。분별대호곤선상행량단선로적궤도불평순진행예측,결과표명해예측방법상대오차평균치분별위2.76%화2.08%,예측결과적후험차비치분별위0.121화0.151,정도등급체도1급。
Effective prediction of the track irregularity development trend can improve the efficiency of railway line maintenance & repairs and so ensure traffic safety.According to track irregularity development character-istics,the combination prediction method based on the non-equal interval weighted grey theory and neural net-work method was proposed.With this method,by constructing the non-equal interval weighted grey prediction model,the average of the original TQI sequence was regarded as the cumulative sequence initial value,the inte-gral area of the continuous accumulation function was used as the background value,the cumulative sequence was processed by weighting.Therefore,the contribution of the time sequence to the track irregularity predic-tion results was better reflected.On this basis,the BP neural network model was introduced to amend the TQI prediction residuals sequence and to overcome the drawback of low prediction accuracy by a single model.The track irregularities of two up-direction sections of the Shanghai-Kunming Line were predicted respectively.The prediction results indicate that the means of the relative errors are 2.76% and 2.08% respectively,the posteri-or error ratios are 0.121 and 0.151 respectively,and the accuracy level reaches A.