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Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 89 - Number 1
Year of Publication: 2014
Authors:
S. Alamelu Mangai
B. Ravi Sankar
K. Alagarsamy
10.5120/15470-4112

Alamelu S Mangai, Ravi B Sankar and K Alagarsamy. Article: Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network. International Journal of Computer Applications 89(1):41-47, March 2014. Full text available. BibTeX

@article{key:article,
	author = {S. Alamelu Mangai and B. Ravi Sankar and K. Alagarsamy},
	title = {Article: Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {89},
	number = {1},
	pages = {41-47},
	month = {March},
	note = {Full text available}
}

Abstract

Modeling and forecasting of a time series data is an integral part of the Data Mining. Sun spot numbers observed on the sun are a good candidate for a time series. A number of linear statistical models are discussed in this paper because Taylor series has similarity with an Auto Regressive model. A new algorithm based on Taylor series expansion and artificial neural network is presented. Based on Taylor series algorithm and ARIMA model, the Sunspot numbers are forecasted and compared.

References

  • Box G. E. P, Jenkins G. M and Reinsel G. C, 1994, "Time Series Analysis, Forecasting and Control", Prentice Hall.
  • G. Peter Zhang, "Time series forecasting using a hybrid ARIMA and neural network model", ELSEVIER, Neurocomputing 50 (2003) 159 – 175.
  • Qiang Yang, Haining Henry Zhang and Hui Zhang, "Taylor Series Prediction: A Cache Replacement Policy based on Second-order Trend Analysis", Hawaii International Conference on System Sciences 01/2001; 5:5023, ISBN 0-7695-0981-9.
  • Hosein Marzi and Mark Turnbull, "Use of Neural Networks in Forecasting Financial Market", 2007 IEEE International Conference on Granular Computing, IEEE Computer Society.
  • Chengqun Yin, Lifeng Kang and Wei Sun, "Hybrid Neural Network Model for Short-Term Load Forecasting", Third International Conference on Natural Computation (ICNC 2007), IEEE Computer Society.
  • Seema Mahajan and Himanshu Mazumdar, "Rainfall Prediction using Neural Net based Frequency Analysis Approach", International Journal of Computer Application, Volume 84 – No 9, December 2013.
  • Salman Quaiyum, Yousuf Ibrahim Khan, Saidur Rahman and Parijat Barman, "Artificial Neural Network based Short Term Load Forecasting of Power Systems", International Journal of Computer Application, Volume 30 – No 4, September 2011
  • McNish. A. G and J. V. Lincoln, Transactions of American Geophysical Union 30 (1949) 673-685.
  • RossIhaka,"Time Series Analysis", available at the URL https://www. stat. auckland. ac. nz/~ihaka/726/notes. pdf
  • George B. Arfken and Hans J. Weber, 2001, "Mathematical Methods for Physicists", pp. 334-340, Academic Press.