Forecasting with temporal hierarchies
Forecasting with temporal hierarchies
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DOI：
10.1016/j.ejor.2017.02.046
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发表时间：
2017-10-01
影响因子：
6.4
通讯作者：
Petropoulos, Fotios
中科院分区：
文献类型：
--
作者：
Athanasopoulos, George;Hyndman, Rob J.;Petropoulos, Fotios
本文介绍了时间序列预测的时间层次的概念。通过非重叠的时间聚集，可以为任何时间序列构造时间层次。在所有聚合级别构建的预测与建议的框架相结合，导致时间上协调，准确和强大的预测。隐含的组合减轻了建模的不确定性，而预测的协调性质产生了统一的预测，支持不同规划范围内的一致决策：从短期运营到长期战略规划。所提出的方法是独立的预测模型。它可以嵌入高层次的管理预测，将复杂和非结构化的信息与较低层次的统计预测。我们的研究结果表明，预测的时间层次结构增加了传统的预测，特别是在建模不确定性增加的准确性。我们讨论了组织的影响，时间调和预测使用的案例研究的事故和紧急部门。(C)2017爱思唯尔B.V.保留所有权利。
This paper introduces the concept of Temporal Hierarchies for time series forecasting. A temporal hierarchy can be constructed for any time series by means of non-overlapping temporal aggregation. Predictions constructed at all aggregation levels are combined with the proposed framework to result in temporally reconciled, accurate and robust forecasts. The implied combination mitigates modelling uncertainty, while the reconciled nature of the forecasts results in a unified prediction that supports aligned decisions at different planning horizons: from short-term operational up to long-term strategic planning. The proposed methodology is independent of forecasting models. It can embed high level managerial forecasts that incorporate complex and unstructured information with lower level statistical forecasts. Our results show that forecasting with temporal hierarchies increases accuracy over conventional forecasting, particularly under increased modelling uncertainty. We discuss organisational implications of the temporally reconciled forecasts using a case study of Accident & Emergency departments. (C) 2017 Elsevier B.V. All rights reserved.