A Neural Network-Based Prediction of Superplasticizers Effect on the Workability and Compressive Characteristics of Portland Pozzolana Cement-Based Mortars

Table 8

Percentage error values of the slump and compressive values from the ANN model.

Percentage of predicted error-values from the ANN framework
Mix ID	Compressive strength					Slump flow
	1 day	3 day	7 day	14 day	28 day	0 min	30 min	60 min	90 min	120 min
M1	1.90	0.87	3.63	−5.90	3.17	−0.75	0.10	−0.80	1.51	−3.61
M2	−2.37	0.82	−4.43	−1.48	−0.48	−1.43	−0.73	0.66	0.50	−2.10
M3	0.48	−4.08	−2.05	8.25	−0.56	0.08	0.75	−1.08	−0.36	−0.77
M4	0.54	2.27	0.26	−4.03	−3.64	−1.22	−0.54	−1.10	−0.89	−1.57
M5	0.86	−0.49	6.02	−6.36	5.39	−1.15	−1.47	−0.81	−0.85	−0.23
M6	−1.56	1.03	−5.26	0.36	3.90	−2.13	1.98	−1.85	4.70	−3.78
M7	8.06	0.93	1.76	−2.80	−3.23	−2.38	−2.70	0.54	2.47	1.18
M8	0.61	−2.54	−3.88	−4.14	−1.71	1.96	2.02	−1.72	2.21	4.29
M9	6.76	0.87	3.23	4.15	−2.59	−1.59	3.06	1.17	3.07	2.61
M10	5.12	1.92	1.55	−2.38	−2.72	1.08	0.73	−1.51	3.12	1.31
M11	2.38	7.46	−5.86	5.71	1.11	2.40	0.88	−1.94	3.37	4.51
M12	−6.07	−2.68	−1.61	−3.31	0.70	−1.58	0.67	−1.29	−1.25	6.23
M13	1.72	1.02	−1.49	−4.06	2.19	2.49	−0.96	3.37	0.64	−2.24
M14	−4.23	−2.55	2.93	1.15	−1.75	−1.65	2.58	2.27	1.72	−1.29
M15	0.83	5.29	0.45	0.86	−2.02	−0.49	−3.11	−3.14	3.55	−5.56