Coupling a Bat Algorithm with XGBoost to Estimate Reference Evapotranspiration in the Arid and Semiarid Regions of China

Table 6

Results of the statistical indicators for all models in the Taiyuan station during the training and testing stages.

Model	Training					Testing
	R^2	RMSE	MAE	RMSEmax10%	MAEmax10%	R^2	RMSE	MAE	RMSEmax10%	MAEmax10%
GPR1	0.812	0.605	0.466	1.34	1.311	0.817	0.714	0.564	1.457	1.451
GPR2	0.972	0.248	0.19	0.561	0.55	0.96	0.418	0.311	0.949	0.942
GPR3	0.97	0.244	0.18	0.594	0.564	0.889	0.534	0.317	1.487	1.328
GPR4	0.972	0.243	0.176	0.582	0.564	0.98	0.403	0.31	0.835	0.827
GPR5	0.976	0.223	0.16	0.545	0.534	0.955	0.391	0.297	0.85	0.842
GPR6	0.978	0.22	0.152	0.559	0.546	0.976	0.397	0.301	0.858	0.851
MARS1	0.949	0.317	0.24	0.712	0.703	0.935	0.497	0.351	1.138	1.115
MARS2	0.97	0.241	0.187	0.542	0.534	0.976	0.377	0.275	0.865	0.853
MARS3	0.974	0.224	0.163	0.551	0.52	0.96	0.377	0.259	0.954	0.884
MARS4	0.984	0.178	0.132	0.422	0.406	0.986	0.364	0.284	0.811	0.803
MARS5	0.982	0.189	0.137	0.453	0.438	0.958	0.385	0.282	0.868	0.859
MARS6	0.988	0.151	0.101	0.39	0.361	0.978	0.33	0.22	0.817	0.809
BAXGB1	0.972	0.241	0.181	0.555	0.542	0.939	0.412	0.302	0.928	0.918
BAXGB2	0.994	0.115	0.087	0.266	0.256	0.97	0.314	0.24	0.712	0.699
BAXGB3	0.984	0.227	0.16	0.556	0.532	0.976	0.259	0.193	0.581	0.58
BAXGB4	0.996	0.097	0.071	0.232	0.221	0.986	0.297	0.235	0.643	0.632
BAXGB5	0.996	0.082	0.063	0.186	0.182	0.964	0.308	0.237	0.722	0.715
BAXGB6	1	0.036	0.026	0.083	0.08	0.988	0.253	0.182	0.594	0.578

Note. Bold font indicates the best model.