A prediction model of the sum of container based on combined BP neural network and SVM

Min-jie Ding, Shao-zhong Zhang, Hai-dong Zhong, Yao-hui Wu and Liang-bin Zhang
Volume: 15, No: 2, Page: 305 ~ 319, Year: 2019
10.3745/JIPS.04.0107
Keywords: BP Neural Network, Grey Relational Analysis, Sum of Container Prediction, Support Vector Machine
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Abstract
The prediction of the sum of container is very important in the field of container transport. Many influencing factors can affect the prediction results. These factors are usually composed of many variables, whose composition is often very complex. In this paper, we use gray relational analysis to set up a proper forecast index system for the prediction of the sum of containers in foreign trade. To address the issue of the low accuracy of the traditional prediction models and the problem of the difficulty of fully considering all the factors and other issues, this paper puts forward a prediction model which is combined with a back-propagation (BP) neural networks and the support vector machine (SVM). First, it gives the prediction with the data normalized by the BP neural network and generates a preliminary forecast data. Second, it employs SVM for the residual correction calculation for the results based on the preliminary data. The results of practical examples show that the overall relative error of the combined prediction model is no more than 1.5%, which is less than the relative error of the single prediction models. It is hoped that the research can provide a useful reference for the prediction of the sum of container and related studies.

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Cite this article
IEEE Style
M. Ding, S. Zhang, H. Zhong, Y. Wu and L. Zhang, "A prediction model of the sum of container based on combined BP neural network and SVM," Journal of Information Processing Systems, vol. 15, no. 2, pp. 305~319, 2019. DOI: 10.3745/JIPS.04.0107.

ACM Style
Min-jie Ding, Shao-zhong Zhang, Hai-dong Zhong, Yao-hui Wu, and Liang-bin Zhang. 2019. A prediction model of the sum of container based on combined BP neural network and SVM, Journal of Information Processing Systems, 15, 2, (2019), 305~319. DOI: 10.3745/JIPS.04.0107.