References
- 마쓰오 유타카 (2015) 인공지능과 딥러닝, (주)동아엠앤비.
- Kim, J., Pyo, H., Ha, J., Lee, C., Kim, J. (2015) "Deep learning algorithms and applications" Communications of the Korean Institute of Information Scientists and Engineers, Korea Information Science Society, 33(8), 2015.8, 25-31.
- Kim, S., Hong, S., Joh, M., Song, S. (2017) "DEEPRAIN: convLSTM network for precipitation prediction using multichannel radar data" 7th International Workshop on Climater Informatict September 20-22.
- Ha, J.H., Lee, Y.H., Kim, Y.H. (2016). "Forecasting the Precipitation of the Next Day Using Deep Learning", Journal of Korean Institute of Intelligent Systems 26(2), 93-98. https://doi.org/10.5391/JKIIS.2016.26.2.093
- Hall, T., Brooks, H.E., Doswell, C. A. (1999) "Precipitation forecasting using a neural network", Weather and Forecasting, vol. 14, no.3, pp. 338-345, 1999. https://doi.org/10.1175/1520-0434(1999)014<0338:PFUANN>2.0.CO;2
- Kuligowski, R.J., 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 https://doi.org/10.1175/1520-0434(1998)013<1194:LPFFAN>2.0.CO;2
- LeCun, Y., Bottou, L., Bengio, Y., Haffner, P. (1998) "Gradient-based learning applied to document recognition" Proceedings of the IEEE, vol. 86, issue 11, pp. 2278-2324, November 1998. https://doi.org/10.1109/5.726791
- Lee, S., Cho, S., Wong, P.M. (1998), "Rainfall prediction using artificial neural networks", Journal of Geographic Information and Decision Analysis, vol. 2, no. 2, pp. 233-242
- Nguyen, M., Nguyen, P., Vo, T., Hoang, L. (2017) "Deep Neural Networks with Residual Connections for Precipitation Forecasting" CIKM 2017, Nov 2017, Singapore
- Seo, J.H., Lee, Y.H., Kim, Y.H. (2012), "Feature selection to predict very short-term heavy rainfall based on differential evolution", Journal of Korean Institute of Intelligent Systems, vol. 22, no. 6, pp. 706-714. https://doi.org/10.5391/JKIIS.2012.22.6.706
- Shenzhen Meteorological Bureau-Alibab, "Short-Term Quantitative Precipitation Forecasting," https://tianchi.aliyun.com/competition/information.htm?spm=5176.100067.5678.2.jsxLyX&raceId=231596
- Shi, X., Chen, Z., Wang, H., Yeung, D., Wong, W., Woo, W. (2015) "Convolutional LSTM network: A machine learning approach for precipitation nowcasting." Advances in Neural Information Processing Systems. 2015.
- Shi X., Gao, Z., Lausen, L., Wang, H., Yeung D., Wong, W., 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, USA.
- Wong, W., Shi, X., Yeung, D., Woo, W. (2016). "A deep-learning method for precipitation nowcasting" WMO WWRP 4th International symposium on nowcasting and very-short-range forecast 2016.
- Yao, Y., Li, Z. (2017) "CIKM AnalytiCup 2017: Short-Term Precipitation Forecasting Based on Radar Reflectivity Images" CIKM 2017, Nov 2017, Singapore.
- Zhang, Z., Wei, S. (2017) "A Method for Short-Term Quantitative Precipitation Forecasting" CIKM 2017, Nov 2017, Singapore.