Sun, J.; Dang, W.; Wang, F.; Nie, H.; Wei, X.; Li, P.; Zhang, S.; Feng, Y.; Li, F.
Prediction of TOC Content in Organic-Rich Shale Using Machine Learning Algorithms: Comparative Study of Random Forest, Support Vector Machine, and XGBoost. Energies 2023, 16, 4159.
https://doi.org/10.3390/en16104159
AMA Style
Sun J, Dang W, Wang F, Nie H, Wei X, Li P, Zhang S, Feng Y, Li F.
Prediction of TOC Content in Organic-Rich Shale Using Machine Learning Algorithms: Comparative Study of Random Forest, Support Vector Machine, and XGBoost. Energies. 2023; 16(10):4159.
https://doi.org/10.3390/en16104159
Chicago/Turabian Style
Sun, Jiangtao, Wei Dang, Fengqin Wang, Haikuan Nie, Xiaoliang Wei, Pei Li, Shaohua Zhang, Yubo Feng, and Fei Li.
2023. "Prediction of TOC Content in Organic-Rich Shale Using Machine Learning Algorithms: Comparative Study of Random Forest, Support Vector Machine, and XGBoost" Energies 16, no. 10: 4159.
https://doi.org/10.3390/en16104159
APA Style
Sun, J., Dang, W., Wang, F., Nie, H., Wei, X., Li, P., Zhang, S., Feng, Y., & Li, F.
(2023). Prediction of TOC Content in Organic-Rich Shale Using Machine Learning Algorithms: Comparative Study of Random Forest, Support Vector Machine, and XGBoost. Energies, 16(10), 4159.
https://doi.org/10.3390/en16104159
