Research on forecast of express freight volume based on optimized BP neural network

Jing Wei; Jian Yang; Chengyuan Fan; Zhongxing Zheng; Xihao Huang

doi:10.1117/12.3012030

7 December 2023 Research on forecast of express freight volume based on optimized BP neural network

Jing Wei, Jian Yang, Chengyuan Fan, Zhongxing Zheng, Xihao Huang

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294157 (2023) https://doi.org/10.1117/12.3012030
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Based on the two tasks of emergency parcel dispatch and optimization of logistics structure of e-commerce network, this paper analyzes and predicts the daily cargo volume of each line in 2023 according to the data of each line and displays the forecast results of three lines with images. The prediction model of line cargo volume was established to predict the daily cargo volume of each line during 2023-01-01 to 2023-01-31, and the prediction results of three lines were given. According to the given data, data cleaning was carried out, and some extreme data were removed through outlier processing. After that, we established a time series prediction model based on BP neural network to predict the historical data of each line. Meanwhile, we also established a gray prediction model for comparative analysis, determined the optimal fitting model, and got the final target prediction results.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jing Wei, Jian Yang, Chengyuan Fan, Zhongxing Zheng, and Xihao Huang "Research on forecast of express freight volume based on optimized BP neural network", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294157 (7 December 2023); https://doi.org/10.1117/12.3012030

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available