| CPC G06F 16/2477 (2019.01) [G06F 16/221 (2019.01); G06F 16/2282 (2019.01)] | 24 Claims |
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1. A computer-implemented method when executed by data processing hardware causes the data processing hardware to perform operations comprising:
receiving a time series forecasting query from a user device, the time series forecasting query requesting the data processing hardware to perform a plurality of time series forecasts, each time series forecast being a forecast of future data based on respective current data;
for each time series forecast of the plurality of time series forecasts requested by the time series forecasting query, simultaneously:
training a plurality of models for the respective time series forecast decomposed into multiple components;
for each respective model of the plurality of models, estimating, by the data processing hardware, using the respective current data, a respective relative quality of the respective model, the respective relative quality representing a quality of the respective model relative to each other model of the plurality of models;
selecting, using the respective relative quality of each respective model without relying on empirical means, one of the plurality of models that best fits the respective time series forecast; and
forecasting the future data based on the selected best fitting model and the respective current data; and
returning, by the data processing hardware, to the user device, the forecasted future data for each of the plurality of time series forecasts requested by the time series forecasting query.
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