A hybrid short-term traffic flow forecasting model based on time series multifractal characteristics-Reference-Cited by-同舟云学术

A hybrid short-term traffic flow forecasting model based on time series multifractal characteristics

Published:2017-12-04 Issue:8 Volume:48 Page:2429-2440
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Zhang Hong,Wang Xiaoming,Cao Jie,Tang Minan,Guo Yirong

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/article/10.1007/s10489-017-1095-9/fulltext.html

Reference24 articles.

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2. Zhang Y, Zhang Y (2016) A comparative study of three multivariate short-term freeway traffic flow forecasting methods with missing data[J]. J Intell Transp Syst 20(3):205–218

3. Ghosh B, Basu B, Mahony MO’ (2009) Multivariate short-term traffic flow forecasting using time-series analysis[J]. IEEE Trans Intell Transp Syst 10(2):246–254

4. Dong C, Xiong Z, Shao C, Zhang H (2015) A spatial-temporal-based state space approach for freeway network traffic flow modelling and prediction [J]. Trans: A Transp Sci 11(7):1–14

5. Tang J, Liu F, Zou Y, Zhang W, Wang Y (2017) An improved fuzzy neural network for traffic speed prediction considering periodic characteristic [J]. IEEE Trans Intell Transp Syst 18(9):2340–2350

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