基于BP神经网络的全社会集装化货物运量预测

doi:10.3976/j.issn.1002０4026.2015.02.012

Abstract

Abstract: We generalize wholly social containerized freight volume from 1995 to 2012. We also screen out indexes with gray correlation analysis method.We further construct BP neural network prediction model, based on which we predict wholly social containerized freight domestic demand from 2013 to 2020.Prediction results show that BP neural network model has better fitting effect for the actual past value and little error. It demonstrates that the model has higher reliability and practicability.

Key words: containerization, freight volume forecast, BP neural network

CLC Number:

U294.3

QIN Jian,HE Shiwei. BP neural network based volume forecast of wholly social containerized freight[J].SHANDONG SCIENCE, 2015, 28(2): 70-74.

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Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits third parties to freely share (i.e., copy and redistribute the material in any medium or format) and adapt (i.e., remix, transform, or build upon the material) the articles published in this journal, provided that appropriate credit is given, a link to the license is provided, and any changes made are indicated. The material may not be used for commercial purposes. For details of the CC BY-NC 4.0 license, please visit: https://creativecommons.org/licenses/by-nc/4.0

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BP neural network based volume forecast of wholly social containerized freight

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