短时公交客流的弦不变量预测方法

doi:10.16451/j.cnki.issn1003-6059.201809007

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Abstract

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.

Key words： String Theory String Invariants Prediction of Short-Term Passenger Flow of Bus Genetic Algorithm Clustering of Temporal Sequences

Received: 19 December 2017

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	Articles by authors
	DONG Hongzhao
	LIU Qian
	FU Fengjie

Cite this article:

DONG Hongzhao,LIU Qian,FU Fengjie. Prediction Method of String Invariants of Short-Term Passenger Flow of Bus[J]. , 2018, 31(9): 845-855.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201809007 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I9/845

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