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Original Articles

Tourist number prediction of historic buildings by singular spectrum analysis

, , &
Pages 827-846 | Received 24 Oct 2013, Accepted 28 Jul 2015, Published online: 25 Sep 2015

References

  • K. Afshar and N. Bigdeli, Data analysis and short term load forecasting in Iran electricity market using singular spectral analysis, Energy. 36 (2011), pp. 2620–2627. doi: 10.1016/j.energy.2011.02.003
  • C. Beneki and B. Eeckels, Signal extraction and forecasting of the UK tourism income time series: A singular spectrum analysis approach, J. Forecast. 31 (2012), pp. 391–400. doi: 10.1002/for.1220
  • C. Beneki and E.S. Silva, Analysing and forecasting European Union energy data, Int. J. Energ. Stat. 11 (2013), pp. 733–747.
  • G.E.P. Box and G.M. Jenkins, Time series analysis: Forecasting and control, J. Bus. 44 (1971), pp. 455–458. doi: 10.1086/295406
  • K.W. Chau and C.L. Wu, A hybrid model coupled with singular spectrum analysis for daily rainfall prediction, J. Hydroinform. 12 (2010), pp. 458–473. doi: 10.2166/hydro.2010.032
  • E.B. Dagum, The X-11-ARIMA seasonal adjustment method, Catalogue No.12-564E, Statistics Canada, 1980.
  • F.X. Diebold and R.S. Mariano, Comparing predictive accuracy, J. Bus. Econ. Stat. 13 (1995), pp. 253–263.
  • S.A. Dyer and J.S. Dyer, Cubic-spline interpolation, IEEE. Instru. Meas. Mag. 4 (2001), pp. 44–46. doi: 10.1109/5289.911175
  • J.B. Elsner and A.A. Tsonis, Singular Spectrum Analysis: A New Tool in Time Series Analysis, Plenum, New York, 1996.
  • K. Fraedrich, Estimating the dimension of weather and climate attractors, J. Atmos. Sci. 43 (1986), pp. 419–432. doi: 10.1175/1520-0469(1986)043<0419:ETDOWA>2.0.CO;2
  • N. Golyandina, V. Nekrutkin, and A. Zhigljavsky, Analysis of Time Series Structure: SSA and Related Techniques, Monographs on statistics and applied probability, Chapman & Hall, Boca Raton, FL, 2001.
  • H. Hassani, Singular spectrum analysis: Methodology and comparison, J. Data Sci. 5 (2007), pp. 239–257.
  • H. Hassani, A. Dionisio and M. Chodsi, The effect of noise reduction in measuring the linear and nonlinear dependency of financial market, Nonlinear Anal.-Real. 11 (2010), pp. 492–502. doi: 10.1016/j.nonrwa.2009.01.004
  • H. Hassani and S. Heravi, Forecasting European industrial production with singular spectrum analysis, Int. J. Forecast. 25 (2009), pp. 103–118. doi: 10.1016/j.ijforecast.2008.09.007
  • H. Hassani, S. Heravi, and A. Zhigljavsky, Forecasting UK industrial production with multivariate singular spectrum analysis, J. Forecast. 32 (2013), pp. 395–408. doi: 10.1002/for.2244
  • H. Hassani and D. Thomakos, A review on singular spectrum analysis for economic and financial time series, Stat. Interf. 3 (2010), pp. 377–397. doi: 10.4310/SII.2010.v3.n3.a11
  • H. Hassani and A. Zhigljavsky, Singular spectrum analysis: Methodology and application to economics data, J. Syst. Sci. Complex. 22 (2009), pp. 372–394. doi: 10.1007/s11424-009-9171-9
  • U. Lall, T. Sangoyomi, and H.D.I. Abarnel, Nonlinear dynamics of the Great Salt Lake: Nonparametric short-term forecasting, Water Resour. Res. 32 (1996), pp. 975–985. doi: 10.1029/95WR03402
  • Q. Li, N.N. Guo, and Z.Y. Han, Application of an autoregressive integrated moving average model for predicting the incidence of Hemorrhagic fever with renal syndrome, Am. J. Trop. Med. Hyg. 87 (2012), pp. 364–370. doi: 10.4269/ajtmh.2012.11-0472
  • C.H. Mao and C.H. Loh, C. H, Application of singular spectrum analysis to structural monitoring and damage diagnosis of bridges, Struct. Infrastruct. E. 10 (2013), pp. 708–727.
  • L. Marrelli, R. Bilato, and P. Franz, Singular spectrum analysis as a tool for plasma fluctuations analysis, Rev. Sci. Instrum. 72 (2001), pp. 499–507. doi: 10.1063/1.1323250
  • V. Moskvina and A. Zhigljavsky, An algorithm based on singular spectrum analysis for change-point detection, Commun. Statistics. Simul. Comput. 32 (2003), pp. 319–352. doi: 10.1081/SAC-120017494
  • K. Patterson and H. Hassani, Multivariate singular spectrum analysis for forecasting revisions to real-time data, J. Appl. Stat. 38 (2011), pp. 2183–2211. doi: 10.1080/02664763.2010.545371
  • M. Qadrdan, M. Ghodsi, and J.Z. Wu, Probabilistic wind power forecasting using a single forecast, Int. J. Energ. Res. 1 (2013), pp. 314–325.
  • M.I. Syam, Cubic spline interpolation predictors over implicitly defined curves, J. Comput. Appl. Math. 157 (2003), pp. 283–295. doi: 10.1016/S0377-0427(03)00411-4
  • N. Yang, T. Guo, and S.S. Law, Experimental study of human-induced effects on floor slab of an ancient Tibetan structure, Earthq. Eng. Eng. Vib. 11 (2012), pp. 513–523. doi: 10.1007/s11803-012-0138-9
  • H.Q. Zhang and J.B. Li, Prediction of tourist quantity based on RBF neural network, J. Comput. 7 (2012), pp. 965–970.
  • C. Zhao, G. Peng, and Q.Y. Yuan, A prediction study on tourist amount based on web search data, IEEE. 2 (2011), pp. 1837–1842.

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