Prediction of air freight volume based on BP neural network
Authors: 
Dechao Han, Yuanyuan PengAuthors Info & Claims
Dechao Han, Yuanyuan PengAuthors Info & ClaimsPages 904 - 907
Abstract
Traffic is particularly important in the development of modern society, and air transport capacity is an important symbol to measure traffic in a region. Based on the review and summary of previous literature, this paper selects five key indicators that affect the air cargo volume to analyze and study the airport cargo volume in the past 21 years by using BP neural network. From the results, it can be seen that a reasonable network structure can accurately predict the freight volume of air transportation, which is helpful to the economic recovery and the further development of civil aviation in China.
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Index Terms
- Prediction of air freight volume based on BP neural network
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Published In
October 2023
1809 pages
ISBN:9798400708305
DOI:10.1145/3650400
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 April 2024
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- Research-article
- Research
- Refereed limited
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EITCE 2023
EITCE 2023: 2023 7th International Conference on Electronic Information Technology and Computer Engineering
October 20 - 22, 2023
Xiamen, China
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Overall Acceptance Rate 508 of 972 submissions, 52%
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