短时公交客流的弦不变量预测方法

短时公交客流预测是智能公交系统动态调度的基础.文中根据短时公交客流数据特性,提出基于弦理论的短时公交客流预测方法,模拟弦结构建立弦不变量客流预测模型(SI-PFPM),并采用遗传算法优化SI-PFPM中各参数.提出基于动态时间弯曲距离的仿射传播(AP)聚类算法,对短时公交客流时间序列进行聚类分析.利用SI-PFPM预测聚类子集数据,并分析预测残差,验证SI-PFPM可以预测短时公交客流的假设成立.最后将SI-PFPM的预测性能与现有方法进行对比分析,验证SI-PFPM对短时公交客流预测的有效性.

Prediction Method of String Invariants of Short-Term Passenger Flow of Bus

The prediction of short-term bus passenger flow is the basis of the dynamic scheduling of the intelligent bus system. Therefore, according to the data characteristics of short-term passenger flow of bus, a short-term bus passenger flow prediction method based on string theory is proposed. A string invariants passenger flow prediction model(SI-PFPM) is constructed by simulating the string structure and the genetic algorithm is adopted to optimize the parameters of SI-PFPM. An AP clustering algorithm (DTW-AP) based on dynamic time warping(DTW) distance is proposed to perform clustering analysis on the passenger flow time series of short-time buses. SI-PFPM is employed to predict the short-term passenger flow data, and the predicted residual error is analyzed. The result shows that SI-PFPM is effective for the prediction of short-term bus passenger flow. Finally, the prediction performance of SI-PFPM is compared with the existing methods, and the effectiveness of SI-PFPM in short-term bus passenger flow prediction is verified.