The Influence and Prediction Analysis of Cargo Volume Under the Change of Logistics Route Based on LSTM Neural Network

Chuyu Yu; Haodi Zhu

doi:10.54097/vtyc2k92

Authors

Chuyu Yu
Haodi Zhu

DOI:

https://doi.org/10.54097/vtyc2k92

Keywords:

LSTM model, Cargo volume prediction, Logistics network, Sorting center.

Abstract

With the vigorous development of e-commerce, logistics industry has put forward higher requirements for the management efficiency of sorting center. Accurately predicting the cargo volume of the sorting center is the key to optimizing personnel scheduling and improving operational efficiency. Aiming at the problem of cargo volume prediction in sorting center of logistics network, this paper constructs a prediction model based on LSTM model.The LSTM model can effectively capture the long-term dependence relationship in the time series data, and the predicted results have a high degree of fitting with the actual results.The research results of this paper show that the cargo volume prediction model based on LSTM model can effectively predict the cargo volume of the logistics network sorting center, and provide decision support for the operation and management of logistics enterprises.

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