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Prediction and analysis of net ecosystem carbon exchange based on gradient boosting regression and random forest

Citations

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Cited by:

  1. Christian Mulomba Mukendi & Hyebong Choi & Suhui Jung & Yun-Seon Kim, 2024. "Determinants of Yearly CO 2 Emission Fluctuations: A Machine Learning Perspective to Unveil Dynamics," Sustainability, MDPI, vol. 16(10), pages 1-28, May.
  2. Tao Shou & Sidan Yao & Qianyu Hong & Jingwen Mao & Yangyang Yuan, 2025. "Impacts of Blue–Green Space Patterns on Carbon Sequestration Benefits in High-Density Cities of the Middle and Lower Yangtze River Basin: A Comparative Analysis Based on the XGBoost-SHAP Model," Land, MDPI, vol. 14(10), pages 1-28, October.
  3. Hung-Ta Wen & Jau-Huai Lu & Deng-Siang Jhang, 2021. "Features Importance Analysis of Diesel Vehicles’ NO x and CO 2 Emission Predictions in Real Road Driving Based on Gradient Boosting Regression Model," IJERPH, MDPI, vol. 18(24), pages 1-28, December.
  4. Yuling Huang & Xiaoping Lu & Chujin Zhou & Yunlin Song, 2023. "DADE-DQN: Dual Action and Dual Environment Deep Q-Network for Enhancing Stock Trading Strategy," Mathematics, MDPI, vol. 11(17), pages 1-27, August.
  5. Deo, Ravinesh C. & Ahmed, A.A. Masrur & Casillas-Pérez, David & Pourmousavi, S. Ali & Segal, Gary & Yu, Yanshan & Salcedo-Sanz, Sancho, 2023. "Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression," Renewable Energy, Elsevier, vol. 203(C), pages 113-130.
  6. Tian, Zhirui & Liu, Weican & Sun, Wenpu & Wu, Chenye, 2025. "From LMP to eLMP: An accurate transfer strategy for electricity price prediction based on learning ensemble," Energy, Elsevier, vol. 325(C).
  7. Xiaodong Li & Ai Ren & Qi Li, 2022. "Exploring Patterns of Transportation-Related CO 2 Emissions Using Machine Learning Methods," Sustainability, MDPI, vol. 14(8), pages 1-21, April.
  8. Jiapeng Cui & Feng Tan, 2022. "PLSR-Based Assessment of Soil Respiration Rate Changes under Aerated Irrigation in Relation to Soil Environmental Factors," Agriculture, MDPI, vol. 13(1), pages 1-15, December.
  9. Yan, Peiliang & Fan, Weijun & Zhang, Rongchun, 2023. "Predicting the NOx emissions of low heat value gas rich-quench-lean combustor via three integrated learning algorithms with Bayesian optimization," Energy, Elsevier, vol. 273(C).
  10. Zifan Huang & Zexia Duan & Yichi Zhang & Tianbo Ji, 2024. "Response of Sustainable Solar Photovoltaic Power Output to Summer Heatwave Events in Northern China," Sustainability, MDPI, vol. 16(12), pages 1-28, June.
  11. 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).
  12. Simin Kheradmand & Nima Heidarzadeh & Seyed Hossein Kia, 2023. "Prediction of the CO2 emission across grassland and cropland using tower-based eddy covariance flux measurements: a machine learning approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 5495-5509, June.
  13. Wang, Kai & Liu, Xing & Guo, Xin & Wang, Jianhang & Wang, Zhuang & Huang, Lianzhong, 2024. "A novel high-precision and self-adaptive prediction method for ship energy consumption based on the multi-model fusion approach," Energy, Elsevier, vol. 310(C).
  14. Zhang, Jinlai & Yang, Wenjie & Chen, Yumei & Ding, Mingkang & Huang, Huiling & Wang, Bingkun & Gao, Kai & Chen, Shuhan & Du, Ronghua, 2024. "Fast object detection of anomaly photovoltaic (PV) cells using deep neural networks," Applied Energy, Elsevier, vol. 372(C).
  15. Juan Luis Martín-Ortega & Javier Chornet & Ioannis Sebos & Sander Akkermans & María José López Blanco, 2024. "Enhancing Transparency of Climate Efforts: MITICA’s Integrated Approach to Greenhouse Gas Mitigation," Sustainability, MDPI, vol. 16(10), pages 1-35, May.
  16. Siddharth Swami & Surindra Suthar & Rajesh Singh & Amit Kumar Thakur & Lovi Raj Gupta & Vineet Singh Sikarwar, 2025. "Integration of anaerobic digestion with artificial intelligence to optimise biogas plant operation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(5), pages 9773-9803, May.
  17. Xiaoxu Guo & Ruibing Kou & Xiang He, 2024. "Towards Carbon Neutrality: Machine Learning Analysis of Vehicle Emissions in Canada," Sustainability, MDPI, vol. 16(23), pages 1-18, November.
  18. R. L. Manogna & Shrey Mehta & Devansh Agarwal, 2026. "Demystifying financial inclusion in an emerging economy: a machine learning approach to index construction and forecasting," Economic Change and Restructuring, Springer, vol. 59(2), pages 1-17, April.
  19. Chen, Haoxuan & Xu, Yinliang & Wu, Wenchuan & Sun, Hongbin, 2025. "Prediction optimization fusion learning-based approach for day-ahead carbon aware scheduling in distribution network," Applied Energy, Elsevier, vol. 397(C).
  20. Rao, Amar & Talan, Amogh & Abbas, Shujaat & Dev, Dhairya & Taghizadeh-Hesary, Farhad, 2023. "The role of natural resources in the management of environmental sustainability: Machine learning approach," Resources Policy, Elsevier, vol. 82(C).
  21. Santhappan, Joseph Sekhar & Boddu, Muralikrishna & Gopinath, Arun S. & Mathimani, Thangavel, 2024. "Analysis of 27 supervised machine learning models for the co-gasification assessment of peanut shell and spent tea residue in an open-core downdraft gasifier," Renewable Energy, Elsevier, vol. 235(C).
  22. Li, Jie & Suvarna, Manu & Pan, Lanjia & Zhao, Yingru & Wang, Xiaonan, 2021. "A hybrid data-driven and mechanistic modelling approach for hydrothermal gasification," Applied Energy, Elsevier, vol. 304(C).
  23. Zhang, Tao & Li, Yiteng & Chen, Yin & Feng, Xiaoyu & Zhu, Xingyu & Chen, Zhangxing & Yao, Jun & Zheng, Yongchun & Cai, Jianchao & Song, Hongqing & Sun, Shuyu, 2021. "Review on space energy," Applied Energy, Elsevier, vol. 292(C).
  24. Roy, Dibyendu & Zhu, Shunmin & Wang, Ruiqi & Mondal, Pradip & Ling-Chin, Janie & Roskilly, Anthony Paul, 2024. "Techno-economic and environmental analyses of hybrid renewable energy systems for a remote location employing machine learning models," Applied Energy, Elsevier, vol. 361(C).
  25. Wood, David A., 2024. "More transparent and explainable machine learning algorithms are required to provide enhanced and sustainable dataset understanding," Ecological Modelling, Elsevier, vol. 498(C).
  26. Yan, Peiliang & Wen, Chuang & Ding, Hongbing & Wang, Xuehui & Yang, Yan, 2025. "The potential of machine learning to predict melting response time of phase change materials in triplex-tube latent thermal energy storage systems," Applied Energy, Elsevier, vol. 390(C).
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