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- University of OklahomaUS5 papers
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- National Astronomical Observatory of JapanJP4 papers
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cs.LG2025
Advanced Torrential Loss Function for Precipitation Forecasting
Jaeho Choi, Hyeri Kim, Kwang-Ho Kim +1
Accurate precipitation forecasting is becoming increasingly important in the context of climate change. In response, machine learning-based approaches have recently gained attentio…
cs.LG2021★ 3 cited
Dynamical prediction of two meteorological factors using the deep neural network and the long short-term memory
Ki-Hong Shin, Jae-Won Jung, Ki-Ho Chang +3
This paper presents the predictive accuracy using two-variate meteorological factors, average temperature and average humidity, in neural network algorithms. We analyze result in f…