Stacked transfer learning for tropical cyclone intensity prediction
Tropical cyclone wind-intensity prediction is a challenging task considering drastic changes
climate patterns over the last few decades. In order to develop robust prediction models, one
needs to consider different characteristics of cyclones in terms of spatial and temporal
characteristics. Transfer learning incorporates knowledge from a related source dataset to
compliment a target datasets especially in cases where there is lack or data. Stacking is a
form of ensemble learning focused for improving generalization that has been recently used …
climate patterns over the last few decades. In order to develop robust prediction models, one
needs to consider different characteristics of cyclones in terms of spatial and temporal
characteristics. Transfer learning incorporates knowledge from a related source dataset to
compliment a target datasets especially in cases where there is lack or data. Stacking is a
form of ensemble learning focused for improving generalization that has been recently used …
Stacked transfer learning for tropical cyclone intensity prediction
R Vikash Deo, R Chandra, A Sharma - arXiv e-prints, 2017 - ui.adsabs.harvard.edu
Tropical cyclone wind-intensity prediction is a challenging task considering drastic changes
climate patterns over the last few decades. In order to develop robust prediction models, one
needs to consider different characteristics of cyclones in terms of spatial and temporal
characteristics. Transfer learning incorporates knowledge from a related source dataset to
compliment a target datasets especially in cases where there is lack or data. Stacking is a
form of ensemble learning focused for improving generalization that has been recently used …
climate patterns over the last few decades. In order to develop robust prediction models, one
needs to consider different characteristics of cyclones in terms of spatial and temporal
characteristics. Transfer learning incorporates knowledge from a related source dataset to
compliment a target datasets especially in cases where there is lack or data. Stacking is a
form of ensemble learning focused for improving generalization that has been recently used …
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