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Adaptive forecasting of time-series

机译:时间序列的自适应预测

摘要

For a time-series, a baseline error value is reduced to compute a target forecast error value by maximizing a net benefit value of a forecasted value of the time-series. For each forecasting model in a set of models, a corresponding model error value related to the time-series is computed. From the set, a subset of models is selected where each model in the subset has a cost that will produce a positive value for the net benefit. A selected model from the subset is associated with the time-series such that a model error value of the selected model is at most equal to the target forecast error. The time-series is forecasted using the selected model such that the forecasted value has an error of less than the baseline error at a future time, and the forecasted value produces a positive net benefit at the future time.
机译:对于时间序列,通过最大化时间序列的预测值的净收益值,减少基线误差值以计算目标预测误差值。对于一组模型中的每个预测模型,计算与时间序列相关的相应模型误差值。从集合中选择模型子集,其中子集中的每个模型的成本都会为净收益产生正值。从子集中选择的模型与时间序列相关联,以使选择的模型的模型误差值最多等于目标预测误差。使用所选模型对时间序列进行预测,以使预测值的误差在将来的时间小于基线误差,并且预测值在将来的时间产生正的净收益。

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