A novel multi-step forecasting strategy for enhancing deep learning models’ performance

Author:

Livieris Ioannis E.ORCID,Pintelas Panagiotis

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference58 articles.

1. An NH, Anh DT (2015) Comparison of strategies for multi-step-ahead prediction of time series using neural network. In 2015 International Conference on Advanced Computing and Applications (ACOMP), pages 142–149. IEEE

2. Atienza R (2018) Advanced Deep Learning with Keras: apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more. Packt Publishing Ltd

3. Maiorino BE, Kampffmeyer MC, Jenssen AR (2017) Recurrent neural networks for short-term load forecasting: an overview and comparative analysis. Springer, Berlin

4. Bontempi G (2008) Long term time series prediction with multi-input multi-output local learning. Proc. 2nd ESTSP, pages 145–154

5. Box GEP, Jenkins GM, Reinsel GC, Ljung GM (2015) Time series analysis: forecasting and control. Wiley, Hoboken

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