Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China-Reference-Cited by-同舟云学术

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Published:2014-07 Issue: Volume:44 Page:110-127
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Jiang Xiushan^ORCID,Zhang Lei,(Michael) Chen Xiqun

Funder

China Railway Corporation

United States National Science Foundation

Publisher

Elsevier BV

Subject

Computer Science Applications,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference56 articles.

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4. Travel time prediction using empirical mode decomposition and gray theory;Chen;Trans. Res. Record: J. Trans. Res. Board,2012

5. The retrieval of intra-day trend and its influence on traffic prediction;Chen;Transp. Res. Part C,2012

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