IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v160y2005i2p501-514.html
   My bibliography  Save this article

Neural network forecasting for seasonal and trend time series

Author

Listed:
  • Zhang, G. Peter
  • Qi, Min

Abstract

No abstract is available for this item.

Suggested Citation

  • Zhang, G. Peter & Qi, Min, 2005. "Neural network forecasting for seasonal and trend time series," European Journal of Operational Research, Elsevier, vol. 160(2), pages 501-514, January.
    • Handle: RePEc:eee:ejores:v:160:y:2005:i:2:p:501-514
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(03)00548-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J V Hansen & R D Nelson, 2003. "Forecasting and recombining time-series components by using neural networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 307-317, March.
    2. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process? Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 396-397, July.
    3. Ghysels, Eric & Granger, Clive W J & Siklos, Pierre L, 1996. "Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 374-386, July.
    4. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 291-320, October.
    5. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    6. Franses, Philip Hans, 1996. "Recent Advances in Modelling Seasonality," Journal of Economic Surveys, Wiley Blackwell, vol. 10(3), pages 299-345, September.
    7. Goodrich, Robert L., 2000. "The Forecast Pro methodology," International Journal of Forecasting, Elsevier, vol. 16(4), pages 533-535.
    8. Gorr, Wilpen L., 1994. "Editorial: Research prospective on neural network forecasting," International Journal of Forecasting, Elsevier, vol. 10(1), pages 1-4, June.
    9. Hylleberg, Svend, 1986. "Seasonality in Regression," Elsevier Monographs, Elsevier, edition 1, number 9780123634559 edited by Shell, Karl.
    10. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Time Series: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 343-349, October.
    11. Franses, Philip Hans & Draisma, Gerrit, 1997. "Recognizing changing seasonal patterns using artificial neural networks," Journal of Econometrics, Elsevier, vol. 81(1), pages 273-280, November.
    12. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    13. Zaiyong Tang & Paul A. Fishwick, 1993. "Feedforward Neural Nets as Models for Time Series Forecasting," INFORMS Journal on Computing, INFORMS, vol. 5(4), pages 374-385, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chu, Ching-Wu & Zhang, Guoqiang Peter, 2003. "A comparative study of linear and nonlinear models for aggregate retail sales forecasting," International Journal of Production Economics, Elsevier, vol. 86(3), pages 217-231, December.
    2. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    3. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2005. "Performance of Seasonal Adjustment Procedures: Simulation and Empirical Results," Econometric Institute Research Papers EI 2005-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Antonio Matas-Mir & Denise R. Osborn & Marco J. Lombardi, 2008. "The effect of seasonal adjustment on the properties of business cycle regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(2), pages 257-278.
    5. Tucker McElroy & Anindya Roy, 2022. "A Review of Seasonal Adjustment Diagnostics," International Statistical Review, International Statistical Institute, vol. 90(2), pages 259-284, August.
    6. Ghiassi, M. & Saidane, H. & Zimbra, D.K., 2005. "A dynamic artificial neural network model for forecasting time series events," International Journal of Forecasting, Elsevier, vol. 21(2), pages 341-362.
    7. Barend Abeln & Jan P. A. M. Jacobs, 2023. "CAMPLET: Seasonal Adjustment Without Revisions," SpringerBriefs in Economics, in: Seasonal Adjustment Without Revisions, chapter 0, pages 7-29, Springer.
    8. Ghysels, E., 1993. "A Time Series Model with Periodic Stochastic Regime Switching," Cahiers de recherche 9314, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    9. Gianluca Cubadda, 2001. "Common Features In Time Series With Both Deterministic And Stochastic Seasonality," Econometric Reviews, Taylor & Francis Journals, vol. 20(2), pages 201-216.
    10. Emanuela Marrocu, 2006. "An Investigation of the Effects of Data Transformation on Nonlinearity," Empirical Economics, Springer, vol. 31(4), pages 801-820, November.
    11. Barend Abeln & Jan P.A.M. Jacobs, 2015. "Seasonal adjustment with and without revisions: A comparison of X-13ARIMA-SEATS and CAMPLET," CIRANO Working Papers 2015s-35, CIRANO.
    12. Franses, Philip Hans & Paap, Richard, 1999. "Does Seasonality Influence the Dating of Business Cycle Turning Points?," Journal of Macroeconomics, Elsevier, vol. 21(1), pages 79-92, January.
    13. Heravi, Saeed & Osborn, Denise R. & Birchenhall, C. R., 2004. "Linear versus neural network forecasts for European industrial production series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 435-446.
    14. Cubadda, Gianluca, 1999. "Common Cycles in Seasonal Non-stationary Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 273-291, May-June.
    15. Méndez Parra, Maximiliano, 2015. "Futures prices, trade and domestic supply of agricultural commodities," Economics PhD Theses 0115, Department of Economics, University of Sussex Business School.
    16. Mendez Parra, Maximiliano, 2015. "Seasonal Unit Roots and Structural Breaks in agricultural time series: Monthly exports and domestic supply in Argentina," MPRA Paper 63831, University Library of Munich, Germany, revised 06 Apr 2015.
    17. Ghysels, Eric, 1994. "On the Periodic Structure of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 289-298, July.
    18. McElroy Tucker, 2021. "A Diagnostic for Seasonality Based Upon Polynomial Roots of ARMA Models," Journal of Official Statistics, Sciendo, vol. 37(2), pages 367-394, June.
    19. Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
    20. Saman, Corina, 2011. "Scenarios of the Romanian GDP Evolution With Neural Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 129-140, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:160:y:2005:i:2:p:501-514. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.