Loss-Customised Probabilistic Energy Time Series Forecasts Using Automated Hyperparameter Optimisation-Reference-Cited by-同舟云学术

Loss-Customised Probabilistic Energy Time Series Forecasts Using Automated Hyperparameter Optimisation

Published:2023-06-16 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 14th ACM International Conference on Future Energy Systems
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Author:

Phipps Kaleb¹^ORCID,Meisenbacher Stefan¹^ORCID,Heidrich Benedikt¹^ORCID,Turowski Marian¹^ORCID,Mikut Ralf¹^ORCID,Hagenmeyer Veit¹^ORCID

Affiliation:

1. Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Germany

Funder

Helmholtz Association

Helmholtz Association?s Initiative and Networking Fund

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3575813.3595204

Reference57 articles.

1. Review of ML and AutoML Solutions to Forecast Time-Series Data

2. Lynton Ardizzone Carsten Lüth Jakob Kruse Carsten Rother and Ullrich Köthe. 2019. Guided Image Generation with Conditional Invertible Neural Networks. (2019). arxiv:1907.02392 Lynton Ardizzone Carsten Lüth Jakob Kruse Carsten Rother and Ullrich Köthe. 2019. Guided Image Generation with Conditional Invertible Neural Networks. (2019). arxiv:1907.02392

3. Mixture EMOS model for calibrating ensemble forecasts of wind speed

4. Christoph Norbert Bergmeir. 2013. New Approaches in Time Series Forecasting: Methods Software and Evaluation Procedures. Ph. D. Dissertation. Universidad de Granada. https://digibug.ugr.es/bitstream/handle/10481/29510/2187699x.pdf Christoph Norbert Bergmeir. 2013. New Approaches in Time Series Forecasting: Methods Software and Evaluation Procedures. Ph. D. Dissertation. Universidad de Granada. https://digibug.ugr.es/bitstream/handle/10481/29510/2187699x.pdf

5. James Bergstra , Rémi Bardenet , Yoshua Bengio , and Balázs Kégl . 2011. Algorithms for Hyper-Parameter Optimization. Advances in Neural Information Processing Systems 24 ( 2011 ). https://proceedings.neurips.cc/paper/2011/file/86e8f7ab32cfd12577bc2619bc635690-Paper.pdf James Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl. 2011. Algorithms for Hyper-Parameter Optimization. Advances in Neural Information Processing Systems 24 (2011). https://proceedings.neurips.cc/paper/2011/file/86e8f7ab32cfd12577bc2619bc635690-Paper.pdf