Agriculture, Journal Year: 2025, Volume and Issue: 15(9), P. 933 - 933

Published: April 25, 2025

Daily reference crop evapotranspiration (ET0) is crucial for precision irrigation management, yet traditional prediction methods struggle to capture its dynamic variations due the complexity and nonlinearity of meteorological conditions. To address this, we propose an Improved Informer model enhance ET0 accuracy, providing a scientific basis agricultural water management. Using soil data from Yingde region, employed Maximal Information Coefficient (MIC) identify key influencing factors integrated Residual Cycle Forecasting (RCF), Star Aggregate Redistribute (STAR), Fully Adaptive Normalization (FAN) techniques into model. MIC analysis identified total shortwave radiation, sunshine duration, maximum temperature at 2 m, 28–100 cm depth, surface pressure as optimal features. Under five-feature scenario (S3), improved achieved superior performance compared Long Short-Term Memory (LSTM) original models, with MAE reduced 0.065 (LSTM: 0.637, Informer: 0.171) MSE 0.007 0.678, 0.060). The inference time was also by 31%, highlighting enhanced computational efficiency. effectively captures periodic nonlinear characteristics ET0, offering novel solution management significant practical implications.

Language: Английский