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RELEVANCE-WEIGHTED FORECASTING BASED ON TIME-SERIES DECOMPOSITION
RELEVANCE-WEIGHTED FORECASTING BASED ON TIME-SERIES DECOMPOSITION
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机译:基于时间序列分解的相关加权预测
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摘要
An input time-series is decomposed into a set of constituent frequencies. For each constituent frequency in a subset of the set of constituent frequencies, a corresponding forecasting model is selected in a subset from a set of forecasting models. From a set of component forecasts produced by the subset of forecasting models, a subset of component forecasts is selected. A component forecast in the subset of component forecasts is selected according to a component forecast selection condition. The subset of component forecasts is output to revise the forecast selection condition. A revised forecast selection condition increases a relevance of a future subset of component forecasts.
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