Predictor fusion for short-term traffic forecasting

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Author(s)

Guo, F

Polak, John W

Krishnamoorthy, Rajesh

Type

Journal Article

Date Issued

2018-07-01

Date Acceptance

2018-04-30

Citation

Transportation Research Part C: Emerging Technologies, 2018, 92, pp.90-100

URI

http://hdl.handle.net/10044/1/59336

DOI

https://www.dx.doi.org/10.1016/j.trc.2018.04.025

ISSN

0968-090X

Publisher

Elsevier

Start Page

90

End Page

100

Journal / Book Title

Transportation Research Part C: Emerging Technologies

Volume

92

Copyright Statement

© 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/

Sponsor

Engineering & Physical Science Research Council (EPSRC)

Engineering & Physical Science Research Council (EPSRC)

EPSRC

Grant Number

EP/F005156/1

EP/I038837/1

EP/I038837/1

Subjects

Science & Technology

Technology

Transportation Science & Technology

Transportation

NEURAL-NETWORK APPROACH

TRAVEL-TIME PREDICTION

FLOW PREDICTION

RANDOM FORESTS

REGRESSION

PERFORMANCE

MODELS

09 Engineering

08 Information And Computing Sciences

15 Commerce, Management, Tourism And Services

Logistics & Transportation

Publication Status

Published

Date Publish Online

2018-05-06