دورية أكاديمية

Research on Container Throughput Forecast Based on ARIMA-BP Neural Network

التفاصيل البيبلوغرافية
العنوان: Research on Container Throughput Forecast Based on ARIMA-BP Neural Network
المؤلفون: Zhang, Yifei, Fu, Yuhui, Li, Genghua
المصدر: Journal of Physics: Conference Series ; volume 1634, issue 1, page 012024 ; ISSN 1742-6588 1742-6596
بيانات النشر: IOP Publishing
سنة النشر: 2020
الوصف: In order to improve the accuracy of the container throughput, the paper proposed a prediction method based on ARIMA-BP neural network for the container throughput, and compared with the combined prediction method based on ARIMA-BP neural network, from the perspective of simple weighting and residual optimization. It is applied to the container throughput prediction of the Qingdao port statistics for a total of 24 quarters from 2014-2019. The results show that the prediction accuracy of the combination prediction method based on residual optimization was the highest. Compared with other prediction models, the evaluation indexes RMSE(Root Mean Square Error), MAE(Mean Absolute Error), and MAPE(Mean Absolute Percentage Error) were 15.95, 13.31 and 2.52% respectively and the prediction accuracy based on the BP neural network was lowest. The prediction method proposed in this paper for container throughput can provide guidance for the related personnel.
نوع الوثيقة: article in journal/newspaper
اللغة: unknown
DOI: 10.1088/1742-6596/1634/1/012024
DOI: 10.1088/1742-6596/1634/1/012024/pdf
الإتاحة: https://doi.org/10.1088/1742-6596/1634/1/012024Test
حقوق: http://creativecommons.org/licenses/by/3.0Test/ ; https://iopscience.iop.org/info/page/text-and-data-miningTest
رقم الانضمام: edsbas.56E2B73
قاعدة البيانات: BASE