The invention discloses a Prophet-DCRNN traffic flow prediction method fusing multi-modal information, and belongs to the technical field of traffic flow prediction. Although an existing flow prediction method based on deep learning well captures time-space characteristics of traffic flow, actual urban traffic is affected by factors such as weather, holidays and festivals, and meanwhile, traffic jam tends to occur in severe weather, holidays and festivals. The provides the Prophet-DCRNN traffic flow prediction method fusing multi-modal information to overcome the defects of the prior art. The method uses a Prophet time sequence prediction algorithm to capture holiday effects, uses a DCRNN to capture traffic space-time characteristics, and in addition, based on a stacking-like technology, the Prophet algorithm, the DCRNN algorithm, holiday characteristics and weather information are fused, a hybrid model that finally fuses multi-modal information is obtained, so the accuracy of traffic prediction in festivals and holidays, severe weather and other scenes is realized.
本发明公开了一种融合多模态信息的Prophet‑DCRNN交通流量预测方法,属于交通流量预测技术领域。现有基于深度学习的流量预测方法虽然很好的捕捉了交通流量的时空特性,然而,实际城市交通还受天气、节假日等因素的影响,同时往往在恶劣天气、节假日更倾向于出现交通拥堵。本发明的目的在于克服现有技术的不足,提供一种融合多模态信息的Prophet‑DCRNN交通流量预测方法,该方法利用Prophet时序预测算法捕获节假日效应,采用DCRNN捕获交通时空特性,此外基于类stacking技术,融合Prophet算法、DCRNN算法及节假日特性、天气信息,得到最终融合多模态信息的混合模型,实现了在节假日、恶劣天气等场景下交通预测的准确性。
Prophet-DCRNN traffic flow prediction method fusing multi-modal information
一种融合多模态信息的Prophet-DCRNN交通流量预测方法
2021-07-02
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES |
Traffic speed prediction in the Lyon area using DCRNN (extended abstract)
TIBKAT | 2020
|Fusing Visual Quantified Features for Heterogeneous Traffic Flow Prediction
DOAJ | 2024
|ROAD TRAFFIC SPEED PREDICTION METHOD FUSING MULTI-FEATURE NEURAL NETWORK
European Patent Office | 2024
|Traffic volume prediction method of Prophet-DeepAR model
European Patent Office | 2023
|