A new time series prediction algorithm based on moving average of nth-order difference

  title={A new time series prediction algorithm based on moving average of nth-order difference},
  author={Yang Lan and Daniel Neagu},
  journal={Sixth International Conference on Machine Learning and Applications (ICMLA 2007)},
As a typical research topic, time series analysis and prediction face a continuously rising interest and have been widely applied in various domains. Current approaches focus on a large number of data collections, using mathematics, statistics and artificial intelligence methods, to process and make a prediction on the next most probable value. This paper proposes a new algorithm using moving average of nth-order difference to predict the next term for pseudo- periodical time series. We use… CONTINUE READING

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Piacentini, “Neural Network Prediction of Solar Activity

  • R. A. Calvo, H. A. Ceccatto, R.D
  • The Astrophysical Journal,
  • 1995
Highly Influential
4 Excerpts

Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks

  • E. W. Saad, D. V. Prokhorov, D.C.II. Wunsch
  • IEEE Transactions on Neural Networks,
  • 1998
1 Excerpt

Matrix Computations, third edition

  • L. Van Golub
  • 1996
1 Excerpt

The Shape of the Sunspot Cycle

  • D. H. Hathaway, R. M. Wilson, E. J. Reichmann
  • Solar Physics,
  • 1994
1 Excerpt

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