基于灰色理论的列车自动运行系统预测模块优化算法

灰色理论在可改进ATO(列车自动运行)速度控制器的算法方面具有可行性和优越性。灰色系统模型主要分为预测模型和决策模型。介绍了传统GM(1,1)灰色预测模型的建立过程,阐述了优化GM(1,1)模型的计算流程和计算过程,并利用实际线路数据检验了优化后的预测模型。检验结果表明,通过优化后的预测模型得到的预测结果平均相对误差小,预测精度高;且同时改进权重系数和初始条件时,预测结果更精确。

Optimization Algorithm for ATO System Forecast Module Based on Grey Theory

There are many advantages of grey theory in the improvement of ATO speed controller algorithm The grey model system consists of forecasting model and decisionmaking model.In the paper,the establishment of traditional GM (1,1) grey forecasting model is introduced,the algorithm process of the optimized GM (1,1) grey model is described,which is examined by the data obtained from actual lines.The examination result shows that the forecasted data by the optimized GM (1,1) grey model has less average relative errors,when the weight coefficient and the initial conditions are improved at the same time,the prediction result will be more accurate.