Firefly Algorithm-Based Artificial Neural Network to Predict the Shear Strength in FRP-Reinforced Concrete Beams

Table 1

Descriptive statistics of the experimental data [7].

	(MPa)	ρf (%)	Ef (GPa)	a/d	(mm)	d (mm)	Vcf (kN)
Mean	41.57	1.07	58300	3.32	284.40	336.79	92.97
Standard deviation	13.08	0.64	42.47	1.44	190.08	210.90	112.77
Min	22.70	0.18	23.20	1.00	89.00	104.00	9.80
Max	88.30	3.43	192.00	12.50	1000.00	1097.00	953.00

Here,  = concrete compressive strength; ρ_f = FRP longitudinal reinforcement ratio; E_f = FRP bar modulus of elasticity; a/d = shear span-to-depth ratio;  = web thickness; d = effective depth; and V_cf = shear strength of the concrete beam.