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An Improved OIF Elman Neural Network and Its Applications to Stock Market

  • Limin Wang
  • Yanchun Liang
  • Xiaohu Shi
  • Ming Li
  • Xuming Han
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4251)

Abstract

An improved model is proposed based on the OIF Elman neural network by introducing direction and time profit factors and applied to the prediction of the composite index of stock. Simulation results show that the proposed model is feasible and effective. Comparisons are also made when the stock exchange is performed using prediction results from different models. It shows that the proposed model could improve the prediction precision evidently and realize the main purpose for investors to obtain more profits.

Keywords

Stock Exchange Composite Index Stock Index Absolute Average Error Ultrasonic Motor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Limin Wang
    • 1
    • 2
  • Yanchun Liang
    • 1
  • Xiaohu Shi
    • 1
  • Ming Li
    • 2
  • Xuming Han
    • 1
    • 3
  1. 1.College of Computer Science and TechnologyJilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of EducationChangchunChina
  2. 2.Department of Computer Science and TechnologyChangchun Taxation CollegeChangchunChina
  3. 3.Institute of Information and Spreading EngineeringChangchun University of TechnologyChangchunChina

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