A Reliability-Based RBF Network Ensemble Model for Foreign Exchange Rates Predication

  • Lean Yu
  • Wei Huang
  • Kin Keung Lai
  • Shouyang Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)


In this study, a reliability-based RBF neural network ensemble forecasting model is proposed to overcome the shortcomings of the existing neural ensemble methods and ameliorate forecasting performance. In this model, the ensemble weights are determined by the reliability measure of RBF network output. For testing purposes, we compare the new ensemble model’s performance with some existing network ensemble approaches in terms of three exchange rates series. Experimental results reveal that the prediction using the proposed approach is consistently better than those obtained using the other methods presented in this study in terms of the same measurements.


Hide Layer Mean Square Error Radial Basis Function Radial Basis Function Network Ensemble Model 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Lean Yu
    • 1
    • 2
  • Wei Huang
    • 3
  • Kin Keung Lai
    • 2
    • 4
  • Shouyang Wang
    • 1
    • 4
  1. 1.Institute of Systems ScienceAcademy of Mathematics and Systems Science, Chinese Academy of SciencesBeijingChina
  2. 2.Department of Management SciencesCity University of Hong KongKowloonHong Kong
  3. 3.School of ManagementHuazhong University of Science and TechnologyWuhanChina
  4. 4.College of Business AdministrationHunan UniversityChangshaChina

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