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A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks

Year 2008, Volume: 37 Issue: 2, 185 - 200, 01.02.2008

References

  • Aladag, C. H. and Egrioglu, E. A forecasting study of time series based on the artificial neural Networks, Proceedings of 14th Statistical Research Conference 2005, 397-406, 2005. [2] Buhamra, S., Smaoui, N. and Gabr, M. The Box-Jenkins analysis and neural networks: Prediction and time series modelling, Applied Mathematical Modelling 27, 805–815, 2003. [3] Egrioglu, E., Aladag, C. H. and Gunay, S. A new model selection strategy in artificial neural networks, Applied Mathematics and Computation 195, 591–597, 2008.
  • Gunay, S., Egrioglu, E. and Aladag, C. H. Introduction to single variable time series analysis (Hacettepe University Press, 2007).
  • Hecth-Nielsen, R. Neurocomputing (Addison-Wesley, Menlo Park, CA., 1990).
  • Hwrang, H. B. Insights into neural network forecasting of the time series corresponding to ARMA(p,q) structures, The International Journal of Management Science 29, 273–289, 2001. [7] Kang, S. An Investigation of the use of feedforward neural networks for forecasting (PhD. Thesis, Kent State University, 1991).
  • Lachtermacher, G. and Fuller, J. D. Backpropagation in time-series forecasting, Journal of Forecastinng 14, 381–393, 1995.
  • Lippmann, R. P. An introduction to computing with neural nets, IEEE ASSP Magazine, April, 4–22, 1987.
  • Picton, P. D. Introduction to Neural Networks (Macmillan Press Ltd., 1994).
  • Sharda, R. and Patil, R .B. Connectionist approach to time series prediction: An emprical test, Journal of Intelligent Manufacturing 3, 317–323, 1991.
  • Tang, Z., Almeıda, C. and Fishwick P. A. Time series forecasting using neural networks vs Box-Jenkins methodology, Simulation 57, 303–310, 1991.
  • Tang, Z. and Fishwick, P. A. Feedforward neural nets as models for time series forecasting, Operations Research Society of America 5, 374–385, 1993.
  • Wong, F. S. Time series forecasting using backpropagation neural networks, Neurocomput- ing 2, 147–159, 1991.
  • Zhang, G. P., Patuwo, B. E. and Hu, Y. M. Forecasting with artificial neural networks: The state of the art, International Journal of Forecasting 14, 35–62, 1998.
  • Zhang, G.P., Patuwo, B. E. and Hu, Y. M. A simulation study of artificial neural networks for nonlinear time-series forecasting, Computers and Operations Research 28, 381–396, 2001. [17] Zhang, G. P. and Qi, M. Neural network forecasting for seasonal and trend time series, European Journal of Operational Research 160, 501–514, 2005.
  • Zurada, J. M. Introduction of artificial neural systems (St. Paul: West Publishing, 1992).

A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks

Year 2008, Volume: 37 Issue: 2, 185 - 200, 01.02.2008

References

  • Aladag, C. H. and Egrioglu, E. A forecasting study of time series based on the artificial neural Networks, Proceedings of 14th Statistical Research Conference 2005, 397-406, 2005. [2] Buhamra, S., Smaoui, N. and Gabr, M. The Box-Jenkins analysis and neural networks: Prediction and time series modelling, Applied Mathematical Modelling 27, 805–815, 2003. [3] Egrioglu, E., Aladag, C. H. and Gunay, S. A new model selection strategy in artificial neural networks, Applied Mathematics and Computation 195, 591–597, 2008.
  • Gunay, S., Egrioglu, E. and Aladag, C. H. Introduction to single variable time series analysis (Hacettepe University Press, 2007).
  • Hecth-Nielsen, R. Neurocomputing (Addison-Wesley, Menlo Park, CA., 1990).
  • Hwrang, H. B. Insights into neural network forecasting of the time series corresponding to ARMA(p,q) structures, The International Journal of Management Science 29, 273–289, 2001. [7] Kang, S. An Investigation of the use of feedforward neural networks for forecasting (PhD. Thesis, Kent State University, 1991).
  • Lachtermacher, G. and Fuller, J. D. Backpropagation in time-series forecasting, Journal of Forecastinng 14, 381–393, 1995.
  • Lippmann, R. P. An introduction to computing with neural nets, IEEE ASSP Magazine, April, 4–22, 1987.
  • Picton, P. D. Introduction to Neural Networks (Macmillan Press Ltd., 1994).
  • Sharda, R. and Patil, R .B. Connectionist approach to time series prediction: An emprical test, Journal of Intelligent Manufacturing 3, 317–323, 1991.
  • Tang, Z., Almeıda, C. and Fishwick P. A. Time series forecasting using neural networks vs Box-Jenkins methodology, Simulation 57, 303–310, 1991.
  • Tang, Z. and Fishwick, P. A. Feedforward neural nets as models for time series forecasting, Operations Research Society of America 5, 374–385, 1993.
  • Wong, F. S. Time series forecasting using backpropagation neural networks, Neurocomput- ing 2, 147–159, 1991.
  • Zhang, G. P., Patuwo, B. E. and Hu, Y. M. Forecasting with artificial neural networks: The state of the art, International Journal of Forecasting 14, 35–62, 1998.
  • Zhang, G.P., Patuwo, B. E. and Hu, Y. M. A simulation study of artificial neural networks for nonlinear time-series forecasting, Computers and Operations Research 28, 381–396, 2001. [17] Zhang, G. P. and Qi, M. Neural network forecasting for seasonal and trend time series, European Journal of Operational Research 160, 501–514, 2005.
  • Zurada, J. M. Introduction of artificial neural systems (St. Paul: West Publishing, 1992).
There are 14 citations in total.

Details

Primary Language Turkish
Journal Section Mathematics
Authors

C. H. Aladag This is me

E. Egrioglu This is me

S. Günay This is me

Publication Date February 1, 2008
Published in Issue Year 2008 Volume: 37 Issue: 2

Cite

APA Aladag, C. H., Egrioglu, E., & Günay, S. (2008). A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks. Hacettepe Journal of Mathematics and Statistics, 37(2), 185-200.
AMA Aladag CH, Egrioglu E, Günay S. A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks. Hacettepe Journal of Mathematics and Statistics. February 2008;37(2):185-200.
Chicago Aladag, C. H., E. Egrioglu, and S. Günay. “A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks”. Hacettepe Journal of Mathematics and Statistics 37, no. 2 (February 2008): 185-200.
EndNote Aladag CH, Egrioglu E, Günay S (February 1, 2008) A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks. Hacettepe Journal of Mathematics and Statistics 37 2 185–200.
IEEE C. H. Aladag, E. Egrioglu, and S. Günay, “A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks”, Hacettepe Journal of Mathematics and Statistics, vol. 37, no. 2, pp. 185–200, 2008.
ISNAD Aladag, C. H. et al. “A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks”. Hacettepe Journal of Mathematics and Statistics 37/2 (February 2008), 185-200.
JAMA Aladag CH, Egrioglu E, Günay S. A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks. Hacettepe Journal of Mathematics and Statistics. 2008;37:185–200.
MLA Aladag, C. H. et al. “A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks”. Hacettepe Journal of Mathematics and Statistics, vol. 37, no. 2, 2008, pp. 185-00.
Vancouver Aladag CH, Egrioglu E, Günay S. A New Architecture Selection Strategy in Solving Seasonal Autoregressive Time Series by Artificial Neural Networks. Hacettepe Journal of Mathematics and Statistics. 2008;37(2):185-200.