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Short-term forecasting of the chloride content in the mineral waters of the Ustroń Health Resort using SARIMA and Holt-Winters models Cover

Short-term forecasting of the chloride content in the mineral waters of the Ustroń Health Resort using SARIMA and Holt-Winters models

Open Access
|Feb 2016

References

  1. Adamowski J., Chan H.F. 2011. A wavelet neural network conjunction model for groundwater level forecasting. J. Hydrol. 407: 28-40.10.1016/j.jhydrol.2011.06.013
  2. Asteriou D., Hall S. 2011. ARIMA Models and the Box-Jenkins Methodology. Applied Econometrics: 265-286.
  3. Balaguer E., Palomares A., Sorie E., Martin- Guerrero J.D. 2008. Predicting service request in support centers based on nonlinear dynamics, ARMA modeling and neural networks. Expert Syst. App. 34: 665-672.
  4. Box G.E.P., Jenkins G.M. 1976. Series Analysis Forecasting and Control. 1st ed. Holden-Day, San Francisco.
  5. Chowaniec J. 1993. Budowa geologiczna i warunki hydrogeologiczne okolic Ustronia z uwzględnieniem wyników otworu chłonnego Ustroń C-1. Ustroń Health Resort Archive, unpublished.
  6. Dubois D., Prade H. 1990. Rough fuzzy sets and fuzzy rough sets. Int. J. General Systems, 17 (2-3): 191-209.
  7. Ediger V., Akar S. 2007. ARIMA forecasting of primary energy demand by fuel in Turkey. Energy Policy, 35: 1701-1708.
  8. Karamouz M., Araghinejad Sh. 2012. Advanced Hydrology. Amirkabir Univ. of Tech. Press.
  9. Kondracki J. 2011. Geografia regionalna Polski. PWN, Warszawa.
  10. Ljung G., Box G. 1978. On a Measure of Lack of Fit in Time Series Models. Biometrika, 66: 67-72.
  11. Malina A. 1994. The Forecasting of Economic Phenomena on the Basis of the Methods of Exponential Smoothing of Time Series. Cracow Rev. Econ. Manage., 440: 15-29.
  12. Menhaj M.B. 2012. Artificial Neural Network. Amirkabir Univ. of Tech. Press.
  13. Mohammadi K., Eslami H.R., Dayyani Sh. 2005. Comparison of regression ARIMA and ANN models for reservoir inflow forecasting using snowmelt equivalent. J. Agric. Sci. Tech., 7: 17-30.
  14. Piłatowska M. 2011. Porównanie kryteriów informacyjnych i predykcyjnych w wyborze modelu. J. Manage. Finance, 4: 499-512.
  15. Piontek K. 2002. Modeling and forecasting financial instruments variability (PhD thesis). Wroc. Uniw. Econ., Wrocław.
  16. Rajchel L., Śliwa T., Waligóra J. 2007. Uwagi o wodach leczniczych Ustronia. Współczesne problemy hydrogeologii, 13, Krynica-Kraków.
  17. R Core Team 2015. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna URL http://www.R-project.org/
  18. Solecki T. 2007. Zastosowanie odwiertów chłonnych w ochronie środowiska na przykładzie uzdrowiska Ustroń. Wiertnictwo, nafta, gaz, 24: 465-473.
  19. Szmukta-Zawadzka M., Zawadzki J. 2012. O metodzie prognozowania brakujących danych w szeregach czasowych o wysokiej częstotliwości z lukami. Metody ilościowe w ekonomii, 13: 212-223.
  20. Tratar L.F. 2013. Improved Holt-Winters method: A case of overnight stays of tourists in Republic of Slovenia. Econ. bus. rev., 16: 5-17.
  21. Valipour M., Banihabib M., Behbahani S. 2013. Comparison of the ARMA, ARIMA and the autoregressive artificial neural networks model in forecasting the monthly inflow of Dez dam reservoir. J. Hydrology, 476: 433-441.10.1016/j.jhydrol.2012.11.017
  22. Waligóra J. 2012. Projekt zagospodarowania złoża wody leczniczej „Ustroń” z utworów dewonu, w granicach obszaru górniczego „Ustroń”. Ustroń Health Resort Archive, unpublished.
  23. Waligóra J., Sołtysiak M. 2011. Zatłaczanie wód pozabiegowych w utwory serii węglanowej dewonu w uzdrowisku Ustroń. Biul. Państ. Inst. Geol., 445: 701-708.
Language: English
Page range: 57 - 65
Published on: Feb 12, 2016
Published by: University of Silesia in Katowice, Faculty of Natural Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2016 Dominika Dąbrowska, Marek Sołtysiak, Jan Waligóra, published by University of Silesia in Katowice, Faculty of Natural Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.