Review of automated time series forecasting pipelines-Reference-Cited by-同舟云学术

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Review of automated time series forecasting pipelines

Published:2022-08-09 Issue:6 Volume:12 Page:
ISSN:1942-4787
Container-title:WIREs Data Mining and Knowledge Discovery
language:en
Short-container-title:WIREs Data Min & Knowl

Author:

Meisenbacher Stefan¹^ORCID,Turowski Marian¹^ORCID,Phipps Kaleb¹^ORCID,Rätz Martin²^ORCID,Müller Dirk²³^ORCID,Hagenmeyer Veit¹^ORCID,Mikut Ralf¹^ORCID

Affiliation:

1. Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein‐Leopoldshafen Germany

2. Institute for Energy Efficient Buildings and Indoor Climate RWTH Aachen University Aachen Germany

3. Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research – Energy Systems Engineering (IEK‐10) Jülich Germany

Funder

Bundesministerium für Wirtschaft und Energie

Deutsche Forschungsgemeinschaft

Helmholtz-Gemeinschaft

Publisher

Wiley

Subject

General Computer Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1475

Reference141 articles.

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2. A review on renewable energy and electricity requirement forecasting models for smart grid and buildings

3. Alzyout M. Alsmirat M. &Al‐Saleh M. I.(2019).Automated ARIMA model construction for dynamic vehicle GPS location prediction. InProceedings of the 2019 Sixth International Conference on Internet of Things:Systems Management and Security (IOTSMS) pp.380–386.https://doi.org/10.1109/IOTSMS48152.2019.8939197

4. Amin A. Grunske L. &Colman A.(2012).An automated approach to forecasting QoS attributes based on linear and non‐linear time series modeling. InProceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering pp.130–139.https://doi.org/10.1145/2351676.2351695

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