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PROCESSING MULTI-HORIZON FORECASTS FOR TIME SERIES DATA

机译:处理时间序列数据的多地位线预测

摘要

Methods, systems, and apparatus, including computer storage media, for performing multi-horizon forecasting on time-series data. A method includes determining short-term temporal characteristics for respective forecasting horizons of one or more time-steps. The determining can include generating, using RNN encoders, encoder vectors based on static covariates, and time-varying input data; and predicting using one or more RNN decoders, a short-term pattern for a respective future time period. The method can also include capturing long-term temporal characteristics for the respective forecasting horizons based on the static covariates, the time-varying input data captured during the respective past time-periods, and the time-varying known future input data.
机译:方法,系统和装置,包括计算机存储介质,用于在时间序列数据上执行多地域预测。一种方法包括确定一个或多个时间步长的各个预测视野的短期时间特征。确定可以包括使用RNN编码器,基于静态协变量的编码器矢量和时变输入数据产生的生成。并预测使用一个或多个RNN解码器,对于相应的未来时间段的短期模式。该方法还可以包括基于静态协变量捕获相应预测视野的长期时间特征,在各个过去的时间周期期间捕获的时变输入数据,以及时间变化已知的未来输入数据。

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