Location-Refining neural network: A new deep learning-based framework for Heavy Rainfall Forecast
暂无分享,去创建一个
Xutao Li | Yunming Ye | Chuyao Luo | Xu Huang | Bowen Zhang
[1] Antonio Jose Homsi Goulart,et al. On data selection for training wind forecasting neural networks , 2021, Comput. Geosci..
[2] Weizhen Jiang,et al. Overview on Failures of Urban Underground Infrastructures in Complex Geological Conditions due to Heavy Rainfall in China during 1994-2018 , 2021, Sustainable Cities and Society.
[3] B. Pradhan,et al. Interpretable and explainable AI (XAI) model for spatial drought prediction. , 2021, The Science of the total environment.
[4] Yunming Ye,et al. A Novel LSTM Model with Interaction Dual Attention for Radar Echo Extrapolation , 2021, Remote. Sens..
[5] Marino Marrocu,et al. Performance Comparison between Deep Learning and Optical Flow-Based Techniques for Nowcast Precipitation from Radar Images , 2020, Forecasting.
[6] Yi Wang,et al. Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping , 2020, Comput. Geosci..
[7] J. Freeman,et al. Content search within large environmental datasets using a convolution neural network , 2020, Comput. Geosci..
[8] Vikram M. Gadre,et al. A comparative study of wavelet-based ANN and classical techniques for geophysical time-series forecasting , 2020, Comput. Geosci..
[9] Yangbo Chen,et al. Risk Assessment of Flood Disaster Induced by Typhoon Rainstorms in Guangdong Province, China , 2019, Sustainability.
[10] Philip S. Yu,et al. PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning , 2018, ICML.
[11] Qian Li,et al. A Method of Weather Radar Echo Extrapolation Based on Convolutional Neural Networks , 2018, MMM.
[12] Wang-chun Woo,et al. Operational Application of Optical Flow Techniques to Radar-Based Rainfall Nowcasting , 2017 .
[13] Seyed-Ahmad Ahmadi,et al. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[14] Dit-Yan Yeung,et al. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.
[15] Sebastiano Battiato,et al. A Robust Image Alignment Algorithm for Video Stabilization Purposes , 2011, IEEE Transactions on Circuits and Systems for Video Technology.
[16] I. Jolliffe,et al. Equitability Revisited: Why the ''Equitable Threat Score'' Is Not Equitable , 2010 .
[17] Georgios D. Evangelidis,et al. Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[18] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[19] I. Zawadzki,et al. Scale-Dependence of the Predictability of Precipitation from Continental Radar Images. Part I: Description of the Methodology , 2002 .
[20] Yoshua Bengio,et al. Convolutional networks for images, speech, and time series , 1998 .
[21] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[22] M. Woo,et al. Rainfall in Guangdong province, South China , 1997 .
[23] Stéphane Laroche,et al. Retrievals of Horizontal Winds from Single-Doppler Clear-Air Data by Methods of Cross Correlation and Variational Analysis , 1995 .
[24] J. Marshall,et al. THE DISTRIBUTION OF RAINDROPS WITH SIZE , 1948 .
[25] Oleg R. Nikitin,et al. All convolutional neural networks for radar-based precipitation nowcasting , 2019, Procedia Computer Science.
[26] P. Carrega. Heavy Rainfall Hazards , 2004 .
[27] Antonis D. Koussis,et al. Flood Forecasts for Urban Basin with Integrated Hydro‐Meteorological Model , 2003 .
[28] Wei Qing. RELATIONSHIP BETWEEN RAIN PATTERN AND MOTION OF TROPICAL CYCLONES MAKING LANDFALL IN GUANGDONG , 2003 .