Prediction of air freight volume based on BP neural network

被引：0

作者：

Han, Dechao ^{[1
]}

Peng, Yuanyuan ^{[1
]}

机构：

[1] Henan Univ Sci & Technol, Luoyang, Henan, Peoples R China

来源：

PROCEEDINGS OF 2023 7TH INTERNATIONAL CONFERENCE ON ELECTRONIC INFORMATION TECHNOLOGY AND COMPUTER ENGINEERING, EITCE 2023 | 2023年

关键词：

BP neural network; Air transport; volume of goods transported;

D O I：

10.1145/3650400.3650553

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：904 / 907

页数：4

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