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Relaxed Hybrid Forecasting and its Application to Railway Passenger Turnover

  • Xuejun Chen
  • Suling Zhu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 138)

Abstract

Conventional hybrid forecasting model has been widely used in various forecasting problems, but the sum of weights is limited to 2. An improved hybrid model named as relaxed hybrid model is proposed in this study, where the weights are relaxed to positive real data. The weights are searched by particle swarm optimization algorithm with compress factor technique. The relaxed hybrid model is employed to railway passenger turnover forecasting. The forecasting results show that our proposed model is an effective model for nonlinear time series forecasting.

Keywords

Relaxed hybrid model Forecasting Railway passenger turnover CFPSO 

Notes

Acknowledgments

This work is financially supported by the Natural Science Research Project of Education Department of Henan Province (2011A110018). The authors would like to thank the reviewers’ suggestions.

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Copyright information

© Springer-Verlag London Limited  2012

Authors and Affiliations

  1. 1.Gansu Meteorological Information and Technique Support and Equipment CentreLanzhouPeople’s Republic of China
  2. 2.School of Mathematics and StatisticsLanzhou UniversityLanzhouPeople’s Republic of China

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