Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete

Table 2

Statistical description of data in model (kg/m³).

Parameters	Cement	Fine/coarse aggregate	Water	Superplasticizer
(a) Total data
Mean	384.35	0.964	173.57	2.35
Standard error	4.92	0.014	0.82	0.14
Median	360	0.922	170	1.25
Mode	360	1.018	170	1
Standard deviation	93.01	0.261	15.56	2.69
Sample variance	8650.50	0.068	242.20	7.25
Kurtosis	0.36	6.453	15.59	2.88
Skewness	0.15	2.129	2.46	1.80
Range	440	1.870	170.08	12
Minimum	160	0.230	132	0
Maximum	600	2.1	302.08	12
Sum	137212.84	344.08	61963.8	837.61
Count	357	357	357	357
(b) Train data
Mean	383.29	0.971	173.73	2.43
Standard error	6.07	0.017	1.09	0.17
Median	360	0.922	170	1.38
Mode	320	1.018	170	1
Standard deviation	95.95	0.276	17.18	2.75
Sample variance	9206.58	0.076	295.08	7.55
Kurtosis	0.60	5.826	14.42	2.97
Skewness	0.20	2.089	2.49	1.83
Range	420	1.870	170.08	12
Minimum	180	0.230	132	0
Maximum	600	2.1	302.08	12
Sum	95823.1	242.79	43431.75	606.44
Count	250	250	250	250
(c) Validation data
Mean	387.04	0.922	172.19	1.98
Standard error	12.47	0.025	1.35	0.33
Median	400	0.903	170	1
Mode	360	0.756	170	1
Standard deviation	95.76	0.189	10.36	2.56
Sample variance	9170.57	0.036	107.26	6.55
Kurtosis	0.23	6.821	0.18	4.75
Skewness	0.18	1.663	0.34	2.19
Range	440	1.221	45.2	12
Minimum	160	0.581	154.8	0
Maximum	600	1.802	200	12
Sum	22835.54	54.380	10159.18	117.09
Count	59	59	59	59
(d) Test data
Mean	390.53	0.909	173.07	2.11
Standard error	12.58	0.022	1.21	0.35
Median	378	0.903	175	1
Mode	360	1.041	180	0.5
Standard deviation	89.87	0.156	8.67	2.47
Sample variance	8076.30	0.024	75.21	6.12
Kurtosis	1.08	0.527	−0.18	2.17
Skewness	0.17	0.612	−0.63	1.66
Range	440	0.733	38.32	10.5
Minimum	160	0.661	154	0
Maximum	600	1.394	192.32	10.5
Sum	19916.87	46.346	8826.8	107.57
Count	51	51	51	51