Optimizing the Mixing Proportion with Neural Networks Based on Genetic Algorithms for Recycled Aggregate Concrete

Table 2

Sample of specified concrete mixing proportions used for NN training.

S/a (%)	Unit content (kg/m^3)				Admixtures (g)		Air (%)	Slump (cm)	Compressive strength (MPa)
	NCA	RCA	NFA	RFA	AE-reducing	AE agent
42	1008.68	0	724.81	0	196	4.9	4.3	21.5	33.71	33.79	33.87
	1008.68	0	652.33	72.48	196	4.9	3.9	22	30.45	28.43	30.43
	706.08	302.60	507.37	217.44	196	2.45	5.8	22	33.64	32.65	33.74
	706.08	302.60	362.405	361.405	196	2.45	2.0	23	35.79	32.80	37.02
	504.34	504.34	362.405	361.405	196	2.45	2.8	25	33.71	36.13	34.38
	504.34	504.34	0	724.81	196	2.45	2.3	20	31.67	31.68	26.35
	0	1008.68	724.81	0	196	2.45	4.5	17	32.22	28.39	28.58
	0	1008.68	652.33	72.48	196	2.45	4.5	20	30.42	28.90	32.34
47	921.73	0	567.77	229.19	196	1.225	6.0	22.5	35.83	36.01	35.44
	921.73	0	405.55	381.97	196	1.225	3.3	10	38.16	38.23	36.16
	645.21	270.14	729.99	76.39	196	1.225	5.6	11	34.91	35.30	33.52
	645.21	270.14	567.77	229.19	196	1.225	4.7	17	35.94	35.03	34.66
	460.86	450.23	567.77	229.19	196	1.225	3.8	22.5	33.70	29.98	35.30
	460.86	450.23	405.55	381.97	196	1.225	3.3	19	32.35	35.48	35.23
	0	900.46	243.33	534.76	196	1.225	2.5	21	34.15	34.11	34.92
	0	900.46	0	763.94	196	1.225	3.5	17	30.52	31.34	33.15
52	834.77	0	807.64	84.52	196	0	7.2	22.5	29.08	30.27	29.99
	834.77	0	628.17	253.26	196	0	6.8	23	27.64	29.29	30.61
	584.34	244.65	897.38	0	196	0	2.1	25	30.65	33.06	34.66
	584.34	244.65	448.69	422.6	196	0	2.8	21	32.87	30.62	29.82
	417.39	407.75	807.64	84.52	196	0	3.4	16.5	32.78	33.13	31.87
	417.39	407.75	628.17	253.26	196	0	3.4	16	33.09	34.03	33.48
	0	815.51	897.38	0	196	0	3.0	14.5	35.60	31.52	32.64
	0	815.51	807.64	84.52	196	0	3.4	15	35.63	29.06	29.97