QPSO-AHES-RC: a hybrid learning model for short-term traffic flow prediction
QPSO-AHES-RC: a hybrid learning model for short-term traffic flow prediction
About this item
Full title
Author / Creator
Li, Zhuoxuan , Cao, Jinde , Shi, Xinli and Huang, Wei
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
Accurate assessment of road conditions can effectively alleviate traffic congestion and guide people’s travel plans, traffic control decisions of transportation departments, and formulation of traffic-related laws and regulations. This paper proposes a quantum particle swarm optimization (QPSO) and adaptive hybrid exponential smoothing with residua...
Alternative Titles
Full title
QPSO-AHES-RC: a hybrid learning model for short-term traffic flow prediction
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_crossref_primary_10_1007_s00500_023_08291_w
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_1007_s00500_023_08291_w
Other Identifiers
ISSN
1432-7643
E-ISSN
1433-7479
DOI
10.1007/s00500-023-08291-w
