A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting
A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting
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DOI：
10.1016/j.ijforecast.2019.03.017
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发表时间：
2020-01-01
影响因子：
7.9
通讯作者：
Smyl, Slawek
中科院分区：
文献类型：
--
作者：
Smyl, Slawek
本文介绍了M4预测竞赛的获奖作品。提交的文件利用了一个动态计算图神经网络系统，使标准指数平滑模型与先进的长短期记忆网络混合成一个共同的框架。其结果是一个混合和分层预测方法。(C)2019年国际预测研究所。Elsevier B.V.出版，保留所有权利。
This paper presents the winning submission of the M4 forecasting competition. The submission utilizes a dynamic computational graph neural network system that enables a standard exponential smoothing model to be mixed with advanced long short term memory networks into a common framework. The result is a hybrid and hierarchical forecasting method. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.