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Genetic Programming Based Approach For Modeling Time Series Data Of Real Systems

Author

Listed:
  • DILIP P. AHALPARA

    (Institute for Plasma Research, Near Indira Bridge, Bhat, Gandhinagar-382428, India)

  • JITENDRA C. PARIKH

    (Physical Research Laboratory, Navrangpura, Ahmedabad-380009, India)

Abstract

Analytic models of a computer generated time series (logistic map) and three real time series (ion saturation current in Aditya Tokamak plasma, NASDAQ composite index and Nifty index) are constructed using Genetic Programming (GP) framework. In each case, the optimal map that results from fitting part of the data set also provides a very good description of the rest of the data. Predictions made using the map iteratively are very good for computer generated time series but not for the data of real systems. For such cases, an extended GP model is proposed and illustrated. A comparison of these results with those obtained using Artificial Neural Network (ANN) is also carried out.

Suggested Citation

  • Dilip P. Ahalpara & Jitendra C. Parikh, 2008. "Genetic Programming Based Approach For Modeling Time Series Data Of Real Systems," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 63-91.
    • Handle: RePEc:wsi:ijmpcx:v:19:y:2008:i:01:n:s0129183108011942
    DOI: 10.1142/S0129183108011942
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