Scientific Reports

Table 6 ML models, hybrid models and input meteorological combinations.

From: Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates

No	Models								Input combinations
No	RF	M5P	XGBoost	LightGBM	RF-M5P	RF-LightGBM	RF-XGBoost	XGBoost-LightGBM	Input combinations
1	RF1	M5P1	XGBoost1	LightGBM1	RF-M5P1	RF-LightGBM1	RF-XGBoost1	XGBoost-LightGBM1	Comb. 1	T_max, T_min, R_s
2	RF2	M5P2	XGBoost2	LightGBM2	RF-M5P2	RF-LightGBM2	RF-XGBoost2	XGBoost-LightGBM2	Comb. 2	T_max, T_min, RH_mean
3	RF3	M5P3	XGBoost3	LightGBM3	RF-M5P3	RF-LightGBM3	RF-XGBoost3	XGBoost-LightGBM3	Comb. 3	T_max, T_min, R_s, U₂
4	RF4	M5P4	XGBoost4	LightGBM4	RF-M5P4	RF-LightGBM4	RF-XGBoost4	XGBoost-LightGBM4	Comb. 4	T_max, T_min, RH_mean, U₂
5	RF5	M5P5	XGBoost5	LightGBM5	RF-M5P5	RF-LightGBM5	RF-XGBoost5	XGBoost-LightGBM5	Comb. 5	T_max, T_min, RH_mean, R_s
6	RF6	M5P6	XGBoost6	LightGBM6	RF-M5P6	RF-LightGBM6	RF-XGBoost6	XGBoost-LightGBM6	Comb. 6	T_max, T_min, RH_mean, R_s, U₂

Back to article page

Search

Advanced search

Quick links