A Hybrid Model for Vessel Traffic Flow Prediction Based on Wavelet and Prophet

Autor: Dangli Wang, Yangran Meng, Shuzhe Chen, Cheng Xie, Zhao Liu
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Journal of Marine Science and Engineering, Vol 9, Iss 11, p 1231 (2021)
Druh dokumentu: article
ISSN: 2077-1312
DOI: 10.3390/jmse9111231
Popis: Accurate vessel traffic flow prediction is significant for maritime traffic guidance and control. According to the characteristics of vessel traffic flow data, a new hybrid model, named DWT–Prophet, is proposed based on the discrete wavelet decomposition and Prophet framework for the prediction of vessel traffic flow. First, vessel traffic flow was decomposed into a low-frequency component and several high-frequency components by wavelet decomposition. Second, Prophet was trained to predict the components, respectively. Finally, the prediction results of the components were reconstructed to complete the prediction. The experimental results demonstrate that the hybrid DWT–Prophet outperformed the single Prophet, long short-term memory, random forest, and support vector regression (SVR). Moreover, the practicability of the new forecasting method was improved effectively.
Databáze: Directory of Open Access Journals