HIGH-SPEED RAILWAY BASED ON GENETIC ALGORITHM FOR PREDICTION OF TRAVEL CHOICE

Long Chen-xu, Li Jing, Gao Yue

Abstract

Genetic algorithm is a new optimizing searching method based on biology evolutionary theory. Just as evolution deals in populations of individuals, genetic algorithms mimic nature by evolving huge churning populations of code, all processing and mutating at once. With the frequency of passenger travel speeding up and passenger's demand to the quality of life higher and higher, passengers have higher and higher demands to the travel. Especially in environment, comfort and quick aspect, different passenger focuses on different aspects, therefore, before the research, we must classify the passenger. This paper applies British Sheffield university GA toolbox, with the application of matlab, finally makes a forecast analysis. Because the forecast analysis is based on the questionnaire during the Spring Festival, so the emphasize on the travel choice made by the passengers in this certain circumstances is necessary. In addition, the forecast analysis will be more or less different with other forecast analysis normally.

References

  1. Zhang Qiang, Wang Bin, Zhang Rui, Xu Chun-xia, 2008. Genetic Glgorithm-Based design for DNA sequences sets. Chinese Journal of Computers, 2008, 31 (12) :2193-2199.
  2. He Wei-hui, Wang Jia-Lin, Hu Long-sheng, 2009. The improvement and application of real-coded multiplepopulation genetic algorithm. Chinese Journal of Geophysics, 2009,52 (10): 2644 2651.
  3. Ma Yong-jie, Ma Yi-de, Jiang Zhao-yuan, Sun Qi-guo, 2009. Fast genetic algorithm and its convergence. Systems Engineering and Electronics. 2009,31 (3) :714-718.
  4. Ding Jian-li, Chen Zeng-qiang, Yuan Zhu-Zhi, 2003. On the Combination of Genetic Algorithm and Ant Algorithm. Journal of Computer Research and Development. 2003,40 (9) :1351-1356.
  5. Xu Yonghua, Huang Lijun, 2008. Improved Genetic Algorithm in milk transport vehicles Road King optimization. Northeast Agricultural University .2008,39 (11) :111-115.
  6. Gong Gu, Zhao Xiang-jun, HAO Guo-sheng, Chen Longgao, 2009. Study and implementation of Genetic Algorithm Based on improvment of search space partition. Journal of Henan University Narural Science. 2009,39 (6) :631-636.
  7. Jiang Yun-cai, Wang Qing-bo, 2004. Application of MATLAB Genetic Algorithm Toolbox. Journal of Jiangxi Electric Voactional and Technical College. 2004,17 (3): 42-44.
  8. Qiang Li-xia, Yan Ying, 2006. Analysis on the Difference of demand for passenger transport of high-speed railways between home and abroad. Railway Transport and Economy. 2006,28(9):18-21.
  9. Wu Qun -qi, Xu Xing, 2007. Mechanism research on travelling choices of passengers. Journal of Chang'an University(Social Science Edition). 2007,9(2) :13-16. The Dvelopment of the world's high-speed railway,2006. Railway Survey and Design. 2006,1: 54- 56.
  10. Chen Zhang-ming, JI Xiao-feng, 2008. Study on features of railway passengers' travel activities. Railway Transport and Economy. 2008,30(11): 23-25.
Download


Paper Citation


in Harvard Style

Chen-xu L., Jing L. and Yue G. (2011). HIGH-SPEED RAILWAY BASED ON GENETIC ALGORITHM FOR PREDICTION OF TRAVEL CHOICE . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-54-6, pages 26-31. DOI: 10.5220/0003433400260031


in Bibtex Style

@conference{iceis11,
author={Long Chen-xu and Li Jing and Gao Yue},
title={HIGH-SPEED RAILWAY BASED ON GENETIC ALGORITHM FOR PREDICTION OF TRAVEL CHOICE},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2011},
pages={26-31},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003433400260031},
isbn={978-989-8425-54-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - HIGH-SPEED RAILWAY BASED ON GENETIC ALGORITHM FOR PREDICTION OF TRAVEL CHOICE
SN - 978-989-8425-54-6
AU - Chen-xu L.
AU - Jing L.
AU - Yue G.
PY - 2011
SP - 26
EP - 31
DO - 10.5220/0003433400260031