Research on Check-In Baggage Flow Prediction for Airport Departure Passengers Based on Improved PSO-BP Neural Network Combination Model

Accurate forecasting of passenger checked baggage traffic is crucial for efficient and intelligent allocation and optimization of airport service resources. A systematic analysis of the influencing factors and prediction algorithms for the baggage flow is rarely included in existing studies. To accu...

Full description

Saved in:

Bibliographic Details
Published in:	Aerospace Vol. 11; no. 11; p. 953
Main Authors:	Jiang, Bo, Zhang, Jian, Fu, Jianlin, Ding, Guofu, Zhang, Yong
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2024
Subjects:	Accuracy air transportation Aircraft Airline passengers Airports Algorithms Back propagation networks Baggage baggage flow Civil aviation combination model Efficiency Flow Forecast accuracy Hypothesis testing Interpolation Luggage Missing data neural network Neural networks Pandemics Passengers prediction algorithm Prediction models Prediction theory Predictions Random variables Software China
ISSN:	2226-4310, 2226-4310
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!