MULTI-MODEL BLENDING OF PROBABILISTIC WEATHER FORECASTS
卷宗概要
发明人
Samuel James Levang; Fran Bartolic
IPC 分类
CPC 分类
Multi-model blending of probabilistic weather forecasts is described. A system segments a first training data set into a plurality of second training data sets each including corresponding subsets of a first output of a first probabilistic model and a second output of a second probabilistic model. The system modifies, for each of the subsets, weights of a machine learning model with. The system generates a control parameter indicative of alignment of the machine learning model with one or more of the plurality of second training data sets, and provides, responsive to the control parameter satisfying a threshold indicative of a level of alignment with the plurality of second training data sets, the machine learning model trained to generate, according to the one or more weights, a weighted output of the first probabilistic model and the second probabilistic model at the first point and the second point.
原文（中文）
Multi-model blending of probabilistic weather forecasts is described. A system segments a first training data set into a plurality of second training data sets each including corresponding subsets of a first output of a first probabilistic model and a second output of a second probabilistic model. The system modifies, for each of the subsets, weights of a machine learning model with. The system generates a control parameter indicative of alignment of the machine learning model with one or more of the plurality of second training data sets, and provides, responsive to the control parameter satisfying a threshold indicative of a level of alignment with the plurality of second training data sets, the machine learning model trained to generate, according to the one or more weights, a weighted output of the first probabilistic model and the second probabilistic model at the first point and the second point.