An innovative adaptive hybrid prediction model based on deep learning methods (CEEMDAN-GRU) for green hydrogen production, In case study: Turkey-Reference-Cited by-同舟云学术

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An innovative adaptive hybrid prediction model based on deep learning methods (CEEMDAN-GRU) for green hydrogen production, In case study: Turkey

Published:2024-01 Issue: Volume:52 Page:1266-1279
ISSN:0360-3199
Container-title:International Journal of Hydrogen Energy
language:en
Short-container-title:International Journal of Hydrogen Energy

Author:

Emeksiz Cem^ORCID,Tan Mustafa^ORCID

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Condensed Matter Physics,Fuel Technology,Renewable Energy, Sustainability and the Environment

Reference73 articles.

1. Hydrogen economy;Ural;The Journal of Global Engineering Studies,2020

2. Union of Concerned Scientists. https://www.ucsusa.org/resources/each-countrys-share-co2-emissions (accessed 2022-February-21).

3. Kyoto protocol. https://unfccc.int/kyoto_protocol (accessed 2022-02-22).

4. Marpol. https://www.marineinsight.com/maritime-law/marpol-convention-shipping/(accessed 2022-02-22).

5. Review of policies encouraging renewable energy integration & best practices;Zeneib;Renew Sustain Energy Rev,2015

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient multi-objective rolling strategy of photovoltaic/hydrogen system via short-term photovoltaic power forecasting;International Journal of Hydrogen Energy;2024-08

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