Gap Filling Method and Estimation of Net Ecosystem CO 2 Exchange in Alpine Wetland of Qinghai–Tibet Plateau
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Hassan, Muhammed A. & Khalil, A. & Kaseb, S. & Kassem, M.A., 2017. "Exploring the potential of tree-based ensemble methods in solar radiation modeling," Applied Energy, Elsevier, vol. 203(C), pages 897-916.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Hongchao Zhang & Tengteng Zhu, 2022. "Stacking Model for Photovoltaic-Power-Generation Prediction," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
- Olubayo M. Babatunde & Josiah L. Munda & Yskandar Hamam, 2020. "Exploring the Potentials of Artificial Neural Network Trained with Differential Evolution for Estimating Global Solar Radiation," Energies, MDPI, vol. 13(10), pages 1-18, May.
- Cai, Jianchao & Xu, Kai & Zhu, Yanhui & Hu, Fang & Li, Liuhuan, 2020. "Prediction and analysis of net ecosystem carbon exchange based on gradient boosting regression and random forest," Applied Energy, Elsevier, vol. 262(C).
- Guosheng Duan & Lifeng Wu & Fa Liu & Yicheng Wang & Shaofei Wu, 2022. "Improvement in Solar-Radiation Forecasting Based on Evolutionary KNEA Method and Numerical Weather Prediction," Sustainability, MDPI, vol. 14(11), pages 1-20, June.
- Hassan, Muhammed A. & Al-Ghussain, Loiy & Ahmad, Adnan Darwish & Abubaker, Ahmad M. & Khalil, Adel, 2022. "Aggregated independent forecasters of half-hourly global horizontal irradiance," Renewable Energy, Elsevier, vol. 181(C), pages 365-383.
- Yang, Dazhi, 2022. "Estimating 1-min beam and diffuse irradiance from the global irradiance: A review and an extensive worldwide comparison of latest separation models at 126 stations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
- Chen, Jiang & Zhu, Weining & Yu, Qian, 2021. "Estimating half-hourly solar radiation over the Continental United States using GOES-16 data with iterative random forest," Renewable Energy, Elsevier, vol. 178(C), pages 916-929.
- Bailek, Nadjem & Bouchouicha, Kada & Hassan, Muhammed A. & Slimani, Abdeldjalil & Jamil, Basharat, 2020. "Implicit regression-based correlations to predict the back temperature of PV modules in the arid region of south Algeria," Renewable Energy, Elsevier, vol. 156(C), pages 57-67.
- Tan, Daniel & Suvarna, Manu & Shee Tan, Yee & Li, Jie & Wang, Xiaonan, 2021. "A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing," Applied Energy, Elsevier, vol. 291(C).
- Gupta, Priya & Singh, Rhythm, 2023. "Combining a deep learning model with multivariate empirical mode decomposition for hourly global horizontal irradiance forecasting," Renewable Energy, Elsevier, vol. 206(C), pages 908-927.
- El-Bakry, M. Medhat & Kassem, Mahmoud A. & Hassan, Muhammed A., 2021. "Passive performance enhancement of parabolic trough solar concentrators using internal radiation heat shields," Renewable Energy, Elsevier, vol. 165(P1), pages 52-66.
- Hoxha, Julian & Çodur, Muhammed Yasin & Mustafaraj, Enea & Kanj, Hassan & El Masri, Ali, 2023. "Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis," Applied Energy, Elsevier, vol. 350(C).
- Abunima, Hamza & Park, Woan-Ho & Glick, Mark B. & Kim, Yun-Su, 2022. "Two-Stage stochastic optimization for operating a Renewable-Based Microgrid," Applied Energy, Elsevier, vol. 325(C).
- Wu, Wei & Tang, Xiaoping & Lv, Jiake & Yang, Chao & Liu, Hongbin, 2021. "Potential of Bayesian additive regression trees for predicting daily global and diffuse solar radiation in arid and humid areas," Renewable Energy, Elsevier, vol. 177(C), pages 148-163.
- Muhammed A. Hassan & Hindawi Salem & Nadjem Bailek & Ozgur Kisi, 2023. "Random Forest Ensemble-Based Predictions of On-Road Vehicular Emissions and Fuel Consumption in Developing Urban Areas," Sustainability, MDPI, vol. 15(2), pages 1-22, January.
- Zhigao Zhou & Aiwen Lin & Lijie He & Lunche Wang, 2022. "Evaluation of Various Tree-Based Ensemble Models for Estimating Solar Energy Resource Potential in Different Climatic Zones of China," Energies, MDPI, vol. 15(9), pages 1-23, May.
- Marzouq, Manal & El Fadili, Hakim & Zenkouar, Khalid & Lakhliai, Zakia & Amouzg, Mohammed, 2020. "Short term solar irradiance forecasting via a novel evolutionary multi-model framework and performance assessment for sites with no solar irradiance data," Renewable Energy, Elsevier, vol. 157(C), pages 214-231.
- Gupta, Priya & Singh, Rhythm, 2023. "Combining simple and less time complex ML models with multivariate empirical mode decomposition to obtain accurate GHI forecast," Energy, Elsevier, vol. 263(PC).
- Feng, Yu & Hao, Weiping & Li, Haoru & Cui, Ningbo & Gong, Daozhi & Gao, Lili, 2020. "Machine learning models to quantify and map daily global solar radiation and photovoltaic power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
- Hassan, Muhammed A. & Abubakr, Mohamed & Khalil, Adel, 2021. "A profile-free non-parametric approach towards generation of synthetic hourly global solar irradiation data from daily totals," Renewable Energy, Elsevier, vol. 167(C), pages 613-628.
More about this item
Keywords
alpine wetland eddy covariance; net ecosystem CO 2 exchange (NEE); machine learning; Reddyproc;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4652-:d:1088879. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.