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ARMA-CIGMN - A neural network model for time series

by Flores João Henrique Ferreira , Engel Paulo Martins
Save 12% Save 12%
Current price ₹3,414.00
Original price ₹3,875.00
Original price ₹3,875.00
Original price ₹3,875.00
(-12%)
₹3,414.00
Current price ₹3,414.00

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Book cover type: Paperback
  • ISBN13: 9783659798849
  • Binding: Paperback
  • Subject: N/A
  • Publisher: LAP Lambert Academic Publishing
  • Publisher Imprint: LAP Lambert Academic Publishing
  • Publication Date:
  • Pages: 128
  • Original Price: GBP 30.63
  • Language: English
  • Edition: N/A
  • Item Weight: 200 grams
  • BISAC Subject(s): Probability & Statistics / General

This book presents a new model of neural network for time series analysis and forecasting: the ARMA-CIGMN (Autoregressive Moving Average Classical Incremental Gaussian Mixture Network) model and its analysis. This model is based on modifications made to a reformulated IGMN, the Classical IGMN (CIGMN). The CIGMN is similar to the original IGMN, but based on a classical statistical approach. The modifications to the IGMN algorithm were made to better fit it to time series. The ARMA-CIGMN model demonstrates good forecasts and the modeling procedure can also be aided by known statistical tools as the autocorrelation (acf) and partial autocorrelation functions (pacf), already used in classical statistical time series modeling and also with the original IGMN algorithm models. The ARMA-CIGMN model was evaluated using known series and simulated data.

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