Development of an adaptive neuro-fuzzy inference system (ANFIS) model to predict sea surface temperature (SST)

Figures & Tables

ANFIS Model	Stage	MAE	MSE	RMSE	MAPE	NSE	R-squared
	Training	1.004	2.190	1.480	6.366	0.885	0.922
SC1	Validation	0.459	1.219	1.104	2.596	0.608	0.831
	Total	1.463	3.409	1.846	8.963	0.846	0.846
	Training	0.800	1.412	1.188	4.725	0.926	0.932
SC2	Validation	0.327	0.751	0.867	1.919	0.758	0.770
	Total	1.127	2.163	1.471	6.644	0.902	0.902
	Training	0.792	1.368	1.169	4.669	0.928	0.934
SC3	Validation	0.328	0.746	0.864	1.924	0.760	0.770
	Total	1.120	2.114	1.454	6.594	0.904	0.905
	Training	0.571	0.725	0.851	3.323	0.962	0.962
SC4	Validation	0.205	0.254	0.504	1.196	0.918	0.900
	Total	0.776	0.978	0.989	4.519	0.956	0.956
	Training	1.057	2.440	1.562	6.664	0.872	0.907
GP1	Validation	0.453	1.164	1.079	2.569	0.625	0.842
	Total	1.510	3.604	1.898	9.233	0.837	0.838
	Training	0.812	1.480	1.217	4.894	0.922	0.929
GP2	Validation	0.339	0.865	0.930	1.975	0.722	0.734
	Total	1.152	2.346	1.532	6.869	0.894	0.894
	Training	0.793	1.443	1.201	4.763	0.924	0.931
GP3	Validation	0.341	0.862	0.928	1.972	0.723	0.736
	Total	1.134	2.305	1.518	6.735	0.896	0.896
	Training	0.486	0.533	0.730	2.709	0.972	0.972
GP4	Validation	0.262	0.677	0.823	1.556	0.782	0.753
	Total	0.748	1.210	1.100	4.265	0.945	0.946

Variable	Mean	Unit	SE	SD	Maximum	Minimum	Correlation with SST
Air Temperature	18.90	°C	0.30	5.37	28.50	5.30	0.91
Evaporation	169.05	mm	4.23	75.32	366.60	29.50	0.75
Precipitation	33.73	mm	2.16	38.50	222.20	0.00	−0.48
SST	18.96	°C	0.26	4.71	26.70	7.50	1.00