پیش‌بینی آنومالی سطح دریا با استفاده از روش تجزیه به توابع حالت‌های ذاتی و شبکه عصبی تابع ‌پایه ‌شعاعی

Ali Ghorbani, M., Khatibi, R., Aytek, A., Makarynskyy, O. and Shiri, J. 2010, Sea water level forecasting using genetic programming and comparing the performance with Artificial Neural Networks. Computers & Geosciences, 36, 620-627.

Andersen, O. B. and Scharroo, R., 2011, Range and Geophysical Corrections in Coastal Regions: And Implications for Mean Sea Surface Determination. In: Vignudelli, S., Kostianoy, A. G., Cipollini, P. & Benveniste, J. (eds.) Coastal Altimetry. Berlin, Heidelberg: Springer Berlin Heidelberg.

Bonaduce, A., Pinardi, N., Oddo, P., Spada, G. and Larnicol, G., 2016, Sea-level variability in the Mediterranean Sea from altimetry and tide gauges. Climate Dynamics, 47, 2851-2866.

Cazenave, A. and Cozannet, G. L., 2014, Sea level rise and its coastal impacts. Earth's Future, 2, 15-34.

Curch, J. A. and White, N. J., 2006, A 20th century acceleration in global sea-level rise. Geophysical Research Letters, 33.

DU, K. L. and Swamy, M. N. S., 2006, Radial Basis Function Networks. In: DU, K. L. & Swamy, M. N. S. (eds.) Neural Networks in a Softcomputing Framework. London: Springer London.

Handoko, E. Y., Fernandes, M. J. and Lázaro, C., 2017, Assessment of Altimetric Range and Geophysical Corrections and Mean Sea Surface Models—Impacts on Sea Level Variability around the Indonesian Seas. Remote Sensing, 9.

Holgate, S. J., 2007, On the decadal rates of sea level change during the twentieth century. Geophysical Research Letters, 34.

Huang, N. E., Shen, Z., Long, S. R., WU, M. C., Shih, H. H., Zheng, Q., Yen, N.-C., Tung, C. C. and LiuU, H. H., 1998, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454, 903-995.

Imani, M., You, R. J. and Kuo, C. Y., 2014, Caspian Sea level prediction using satellite altimetry by artificial neural networks. International Journal of Environmental Science and Technology, 11, 1035-1042.

Leuliette, E. W., Nerem, R. S. and Mitchum, G. T., 2004, Calibration of TOPEX/Poseidon and Jason Altimeter Data to Construct a Continuous Record of Mean Sea Level Change. Marine Geodesy, 27, 79-94.

Rahmstorf, S., 2007, A Semi-Empirical Approach to Projecting Future Sea-Level Rise. Science, 315, 368.

Röske, F., 1997, Sea level forecasts using neural networks. Deutsche Hydrographische Zeitschrift, 49, 71-99.

Slangen, A. B. A., Katsman, C. A., Van de wal, R. S. W., Vermeersen, L. L. A. and Riva, R. E. M., 2012, Towards regional projections of twenty-first century sea-level change based on IPCC SRES scenarios. Climate Dynamics, 38, 1191-1209.

Stammer D, C. A., 2018, Satellite Altimetry Over Oceans And Land Surfaces.

Sun, W. and Wang, Q., 2012, Sea level anomaly forecasting based on combined model of least square and arma. Journal of Geodesy and Geodynamics, 32, 91-94.

Vaziri, M., 1997, Predicting Caspian Sea Surface Water Level by ANN and ARIMA Models. Journal of Waterway, Port, Coastal, and Ocean Engineering, 123, 158-162.

Wild, M., Calanca, P., Scherrer, S. C. and Ohmura, A., 2003, Effects of polar ice sheets on global sea level in high-resolution greenhouse scenarios. Journal of Geophysical Research: Atmospheres, 108.

Xiao-Fen, D., 2014, Methodology and Case Study of Sea Level Prediction Based on Secular Tide Gauge Data. 2014.

Zhao, J., Fan, Y. and Mu, Y. 2019, Sea Level Prediction in the Yellow Sea From Satellite Altimetry With a Combined Least Squares-Neural Network Approach. Marine Geodesy, 42, 344-366.