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- © Vilnius University, 2002-2022
- © Brno University of Technology, 2002-2022
- © University of Latvia, 2002-2022
Article
LOAD FLOW PREDICTION OF INTELLIGENT LOGISTICS TRANSPORTATION NETWORK BASED ON LSTM ALGORITHM
Chenyang Zhao, Shiyan Xu, Maoguo Wu, Shuqi Yao, Xiao Luo
ABSTRACT. As a major part of logistics activities, the transportation network significantly impacts logistics efficiency. The complex networks research method is one of the mainstream methods to analyze transportation complexity. However, due to the characteristics of large cities, the contradiction between the enormous logistics distribution demand and the limited road traffic capacity is becoming increasingly apparent in central cities. Therefore, the prediction and research of road load flow are necessary. In this study, the reliability of urban logistics distribution networks is analyzed by considering highway transportation flow. After analysis, we propose to use the Long Short-term Memory algorithm to calculate and predict the intelligent logistics transportation network load flow in the future.
KEYWORDS: LSTM algorithm, intelligent logistics, transportation network.
JEL classification: C44, L92, R41.