Using support vector machine to deal with the missing of solar radiation data in daily reference evapotranspiration estimation in China.

MLA

Chen, Shang, et al. “Using Support Vector Machine to Deal with the Missing of Solar Radiation Data in Daily Reference Evapotranspiration Estimation in China.” Agricultural & Forest Meteorology, vol. 316, Apr. 2022, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.agrformet.2022.108864.

APA

Chen, S., He, C., Huang, Z., Xu, X., Jiang, T., He, Z., Liu, J., Su, B., Feng, H., Yu, Q., & He, J. (2022). Using support vector machine to deal with the missing of solar radiation data in daily reference evapotranspiration estimation in China. Agricultural & Forest Meteorology, 316, N.PAG. https://doi.org/10.1016/j.agrformet.2022.108864

Chicago

Chen, Shang, Chuan He, Zhuo Huang, Xijuan Xu, Tengcong Jiang, Zhihao He, Jiandong Liu, et al. 2022. “Using Support Vector Machine to Deal with the Missing of Solar Radiation Data in Daily Reference Evapotranspiration Estimation in China.” Agricultural & Forest Meteorology 316 (April): N.PAG. doi:10.1016/j.agrformet.2022.108864.