Optimising the Selection of Input Variables to Increase the Predicting Accuracy of Shear Strength for Deep Beams

Table 7

The statistical description of the proposed models using GAITH.

Model	Training phase				Testing phase
	MAE (kN)	RMSE (kN)	NSE	WI	MAE (kN)	RMSE (kN)	NSE	WI
	7.934	17.599	0.984	0.996	37.052	58.095	0.940	0.985
	16.656	30.707	0.952	0.987	48.841	90.397	0.854	0.949
	37.119	51.348	0.865	0.963	63.395	102.509	0.813	0.934
	25.233	33.696	0.942	0.985	48.096	73.227	0.904	0.972
	7.277	17.217	0.985	0.996	33.617	49.519	0.956	0.988
	16.683	28.597	0.958	0.988	47.823	83.513	0.876	0.957
	37.201	51.366	0.865	0.963	62.842	101.058	0.818	0.937
	20.898	28.153	0.959	0.990	54.135	80.528	0.884	0.966
	8.985	18.180	0.983	0.996	34.583	52.704	0.951	0.986
	17.898	35.099	0.937	0.981	55.390	111.414	0.779	0.914
	37.641	51.961	0.862	0.962	62.530	101.179	0.818	0.936
	22.415	30.417	0.953	0.988	50.890	75.503	0.898	0.969
	11.650	20.318	0.979	0.995	35.284	59.671	0.937	0.981
	17.444	27.220	0.962	0.990	43.132	69.895	0.913	0.972
	38.457	54.231	0.849	0.958	66.434	115.355	0.763	0.911
	15.754	23.483	0.972	0.993	47.852	70.912	0.910	0.975
	37.165	49.937	0.872	0.963	62.673	117.293	0.755	0.907
	20.321	35.994	0.934	0.981	59.634	97.587	0.830	0.938
	50.638	71.069	0.741	0.919	76.135	140.787	0.647	0.851
	22.061	30.406	0.953	0.988	59.217	114.584	0.766	0.923