A hybrid optimized model for predicting evapotranspiration in early and late rice based on a categorical regression tree combination of key influencing factors

Long Zhao, Shunhao Qing, Jiayi Bai, Haohao Hao, Hui Li, Yi Shi, Xuguang Xing, Ru Yang. A hybrid optimized model for predicting evapotranspiration in early and late rice based on a categorical regression tree combination of key influencing factors. Computers and Electronics in Agriculture, 211:108031, August 2023. [doi]

@article{ZhaoQBHLSXY23,
  title = {A hybrid optimized model for predicting evapotranspiration in early and late rice based on a categorical regression tree combination of key influencing factors},
  author = {Long Zhao and Shunhao Qing and Jiayi Bai and Haohao Hao and Hui Li and Yi Shi and Xuguang Xing and Ru Yang},
  year = {2023},
  month = {August},
  doi = {10.1016/j.compag.2023.108031},
  url = {https://doi.org/10.1016/j.compag.2023.108031},
  researchr = {https://researchr.org/publication/ZhaoQBHLSXY23},
  cites = {0},
  citedby = {0},
  journal = {Computers and Electronics in Agriculture},
  volume = {211},
  pages = {108031},
}