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NTIS 바로가기Journal of Korea Water Resources Association = 한국수자원학회논문집, v.53 no.12, 2020년, pp.1159 - 1172
윤성심 (한국건설기술연구원 국토보전연구본부) , 박희성 (한국건설기술연구원 국토보전연구본부) , 신홍준 (한국수력원자력(주) 중앙연구원)
This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwa...
Agrawal, S., Barrington, L., Bromberg, C., Burge, J., Gazen, C., and Hickey, J. (2019). Machine learning for precipitation nowcasting from radar images. accessed 08 December 2020, .
Ayzel, G., Scheffer, T., and Heistermann, M. (2020). "RainNet v1.0: A convolutional neural network for radar-based precipitation nowcasting." Geoscientific Model Development, Vol. 13, pp. 2631-2644.
Badrinarayanan, V., Kendall, A., and Cipolla, R. (2017). "SegNet: A deep convolutional encoder-decoder architecture for image segmentation." IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 39, pp. 2481-2495.
Bellon, A., and Austin, G.L. (1978). "The evaluation of two years of real-time operation of a short-term precipitation forecasting procedure (SHARP)." Journal of Applied Meteorology and Climatology, Vol. 17, pp. 1778-1787.
Dahl, G.E., Sainath, T.N., and Hinton, G.E. (2013). "Improving deep neutral networks for LVCSR using rectified linear units and dropout." Proceedings 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, Canada, pp. 8609-8613.
Dixon, M., and Wiener, G. (1993). "TITAN: Thunderstorm identification, tracking, analysis, and nowcasting-a radar-based methodology." Journal of Atmospheric and Oceanic Technology, Vol. 10, pp. 785-797.
Handwerker, J. (2002). "Cell tracking with TRACE3D - a new algorithm." Atmospheric Research, Vol. 61, pp. 15-34.
Hilst, G.R., and Russo, J.A. (1960). An objective extrapolation technique for semiconservative fields with an application to radar patterns. Tech. Memo. No. 3, Travelers Weather Research Center, Hartford, CT, U.S.
Iglovikov, V., and Shvets, A. (2018). TernausNet: U-Net with VGG11 Encoder pre-trained on imagenet for image segmentation. accessed 08 December 2020, .
Johnson, J.T., MacKeen, P.L., Witt, A., DeWayne Mitchell, E., Stumpf, G.J., Eilts, M.D., and Thomas, K.W. (1998). "The storm cell identification and tracking algorithm: An enhanced WSR88D algorithm." Weather and Forecasting, Vol. 13, pp. 263-276.
Kessler, E., and Russo, J.H. (1963). "A program for the assembly and display of radar-echo distributions." Journal of Applied Meteorology and Climatology, Vol. 2, pp. 582-593.
Kingma, D.P., and Ba, J. (2015). "Adam: A method for stochastic optimization." Proceedings 3rd International Conference on Learning Representations. ICLR 2015, San Diego, CA, U.S.
Krizhevsky, A., Sutskever, I., and Hinton, G.E. (2012). "ImageNet classification with deep convolutional neural networks." Advances in neural information processing systems, Vol. 25, No. 2, doi: 10.1145/3065386.
Kuligowski, R.J., and Barros, A.P. (1998). "Localized precipitation forecasts from a numerical weather prediction model using artificial neural networks." Weather and Forecasting, Vol. 13, No. 4, pp. 1194-1204.
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998) "Gradient-based learning applied to document recognition." Proceedings of the IEEE, Vol. 86, No. 11, pp. 2278-2324.
Lee, S., Cho, S., and Wong, P.M. (1998), "Rainfall prediction using artificial neural networks." Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, pp. 233-242.
Lin, C., Vasic, S., Kilambi, A., Turner, B., and Zawadzki, I. (2005). "Precipitation forecast skill of numerical weather prediction models and radar nowcasts." Geophysical Research Letters, Vol. 32, p. L14801, doi: 10.1029/2005GL023451.
Marshall, J.S., and Palmer, W.M. (1948). "The distribution of raindrops with size." Journal of Meteorology, Vol. 5, pp. 165-166.
Nair, V., and Hinton, G.E. (2010). "Interpersonal informatics: Making social influence visible." Proceedings of the 27th International Conference on Machine Learning, Omnipress, Haifa, Israel, pp. 807-814.
Nakakita, E., Ikebuchi, S., Nakamura, T., Kanmuri, M., Okuda, M., Yamaji, A., and Takasao T. (1996). "Short-term rainfall prediction method using a volume scanning radar and GPV data from numerical weather prediction." Journal of Geophysical Research, Vol. 101, No. D21, pp. 26181-26197.
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., and Prabhat. (2019). "Deep learning and process understanding for data-driven Earth system science." Nature, 566, pp. 195-204, doi: 10.1038/s41586-019-0912-1.
Reyniers, M. (2008). "Quantitative precipitation forecasts based on radar observations: Principles, algorithms and operational systems." Royal Meteorological Institute, Belgium.
Rinehart, R.E., and Garvey, E.T. (1978). "Three-dimensional storm motion detection by conventional weather radar." Nature, Vol. 273, pp. 287-289.
Shi, X., Chen, Z., Wang, H., Yeung, D., Wong, W., and Woo, W. (2015). Convolutional LSTM network: A machine learning approach for precipitation nowcasting, accessed 8 December 2020, .
Shi, X., Gao, Z., Lausen, L., Wang, H., Yeung D., Wong, W., and Woo, W. (2017) "Deep learning for precipitation nowcasting: A benchmark and a new model." 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, U.S.
Shiiba, M., Takasao, T., and Nakakita, E. (1984). "Investigation of short-term rainfall prediction method by a translation model." Proceeding 28th Japanese Conference on Hydraulics, JSCE, pp. 423-428.
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., and Salakhutdinov, R. (2014). "Dropout: A simple way to prevent neural networks from overfitting." The Journal of Machine Learning Research, Vol. 15, No. 1, pp. 1929-1958.
Srivastava, R.K., Greff, K., and Schmidhuber, J. (2015). "Training very deep networks." Advances in Neural Information Processing Systems, Curran Associates, Inc., Red Hook, NY, U.S., pp. 2377-2385.
Sugimoto, S., Nakakita E., and Ikebuchi, S. (2001). "A stochastic approach to short-term rainfall prediction using a physically based conceptual rainfall model." Journal of Hydrology, Vol. 242, pp. 137-155.
Sun, J., Xue, M., Wilson, J.W., Zawadzki, I., Ballard, S.P., Onvlee Hooimeyer, J., Joe, P., Barker, D.M., Li, P.-W., Golding, B., Xu, M., and Pinto, J. (2014). "Use of NWP for nowcasting convective precipitation: Recent progress and challenges." Bulletin of the American Meteorological Society, Vol. 95, pp. 409-426, doi: 10.1175/BAMS-D-11-00263.1.
Sutskever, I., Vinyals, O., and Le, Q.V. (2014). "Sequence to sequence learning with neural networks." Advances in Neural Information Processing Systems 27, Curran Associates, Inc., Red Hook, NY, U.S., pp. 3104-3112.
Tran, Q.K., and Song, S.K. (2019). "Computer vision in precipitation nowcasting: Applying image quality assessment metrics for training deep neural networks." Atmosphere, Vol. 10, p. 244.
Tuttle, J., and Gall, R. (1999). "A single-radar technique for estimating the winds in tropical cyclones." Bulletin of the American Meteorology Society, Vol. 80, pp. 653-668.
Tuttle, J.D., and Foote, G.B. (1990). "Determination of boundary layer airflow from a single doppler radar." Journal of Atmospheric and Oceanic Technology, Vol. 7, pp. 218-232.
Xu, H., and Ge, D. (2020). "A novel image edge smoothing method based on convolutional neural network." International Journal of Advanced Robotic Systems, SAGE journals, Vol.17, No. 3, pp.1-11, doi: 10.1177/1729881420921676.
Yoon, S.S. (2019). "Adaptive blending method of radar-based and numerical weather prediction QPFs for urban flood forecasting." Remote Sensing, Vol. 11, p. 642.
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