Comparing lazy and eager learning models for water level forecasting in river-reservoir basins of inundation regions
Lazy and eager learning models are modeled for water level forecasting in rivers. Lazy learning models, LWR and kNN are presented. Eager learning models, ANN, SVR, and regression are compared with LWR and kNN. The 50 historical typhoons that affected the studied watershed are collected. The distinct approximators of models cause the performance to be dependent on individual models.
eager learning water level basin lazy learning prediction