Short-term forecasting optimization algorithms for wind speed along Qinghai-Tibet railway based on different intelligent modeling theories-Reference-Cited by-同舟云学术

Short-term forecasting optimization algorithms for wind speed along Qinghai-Tibet railway based on different intelligent modeling theories

Published:2009-08 Issue:4 Volume:16 Page:690-696
ISSN:1005-9784
Container-title:Journal of Central South University of Technology
language:en
Short-container-title:J. Cent. South Univ. Technol.

Author:

Liu Hui,Tian Hong-qi,Li Yan-fei

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

http://link.springer.com/content/pdf/10.1007/s11771-009-0114-3.pdf

Reference20 articles.

1. TIAN Hong-qi, MIAO Xiu-juan, GAO Guang-jun. Aerodynamic performance of sidewall shape of boxcar under strong crosswind [J]. Journal of Traffic and Transportation Engineering, 2006, 6(3): 5–8. (in Chinese)

2. ZHOU Dan, TIAN Hong-qi, YANG Ming-zhi, LU Zhai-jun. Comparison of aerodynamic performance of different kinds of wagons running on embankment of the Qinghai-Tibet Railway under strong cross-wind [J]. Journal of the China Railway Society, 2007, 29(5): 32–36. (in Chinese)

3. TIAN Hong-qi. Study evolvement of train aerodynamics in China [J]. Journal of Traffic and Transportation Engineering, 2006, 6(1): 1–9. (in Chinese)

4. GAO Guang-jun, TIAN Hong-qi, YAO Song, LIU Tang-hong, BI Guang-hong. Effect of strong cross-wind on the stability of trains running on the Lanzhou-Xinjiang railway line [J]. Journal of the China Railway Society, 2004, 26(4): 36–40. (in Chinese)

5. LI Yan-fei, LIANG Xi-feng, GAO Guang-jun, LIU Tang-hong. Influence of cross-wind on aerodynamic performances of high-speed container flat car running on embankment [J]. Journal of Railway Science and Engineering, 2007, 4(5): 78–82. (in Chinese)

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