Hierarchical Fuzzy Systems Integrated with Particle Swarm Optimization for Daily Reference Evapotranspiration Prediction: a Novel Approach

Reference evapotranspiration (ET0) is a crucial element for deriving irrigation scheduling of major crops. Thus, precise projection ET0 essential better management scarce water resources in many parts the globe. This study evaluates potential Hierarchical Fuzzy System (HFS) optimized by Particle Swarm Optimization (PSO) algorithm (PSO-HFS) to predict daily ET0. The meteorological variables and estimated (using FAO-56 Penman–Monteith equation) were employed as inputs outputs, respectively, PSO-HFS model. prediction accuracy was compared with that Inference (FIS), M5 Model Tree (M5Tree), Regression (RT) Ranking models performed using concept Shannon’s Entropy accounts set performance evaluation indices. Results revealed model (with weight = 0.93) than benchmark (Entropy weights 0.77, 0.74, 0.90 FIS, RT, M5Tree, respectively). Furthermore, generalization capabilities proposed evaluated dataset from test station. Generalization performances equally well unseen provided superior R 0.93, RMSE 0.59 mm d−1 IOA 0.94) while RT 0.82, d−1, 0.83) exhibited worst dataset. overall results imply could effectively be utilized quite efficiently accurately.