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A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting - 2020

A Hybrid Method Of Exponential Smoothing And Recurrent Neural Networks For Time Series Forecasting

Research Area:  Machine Learning


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.


Author(s) Name:  SlawekSmyl

Journal name:  International Journal of Forecasting

Conferrence name:  

Publisher name:  Elsevier

DOI:  10.1016/j.ijforecast.2019.03.017

Volume Information:  Volume 36, Issue 1, January–March 2020, Pages 75-85