IWA Publishing

For the invoking of data mining models, a total of 60 observations of OTE₂₀ are determined employing the weirs with different discharge per unit width (q), porosity (n), mean size (d₅₀)_, and drop height (h). Two groups are created from the total observations for training (70% observations) and testing (30%). Data grouping is carried out randomly. The statistical characteristics of both groups of data are described in Table 2.

Table 2

Statistical character of datasets

Variables	q (m²/s)	d₅₀ (mm)	h (m)	n (%)	OTE₂₀
	Training dataset
Mean	0.01	13.71	0.92	34.63	0.61
Median	0.01	15.59	0.92	40.88	0.62
Std. deviation	0.01	6.36	0.02	16.82	0.11
Variance	0.00	40.47	0.00	282.75	0.01
Kurtosis	−1.61	1.13	−0.51	0.49	0.08
Skewness	−0.11	−1.65	0.55	−1.37	−0.35
Minimum	0.01	0.00	0.90	0.00	0.34
Maximum	0.02	18.32	0.96	49.10	0.86
Count	42	42	42	42	42
	Test dataset
Mean	0.012	13.71	0.92	34.63	0.60
Median	0.01	15.59	0.92	40.88	0.58
Std. deviation	0.01	6.47	0.01	17.10	0.08
Variance	0.00	41.83	0.00	292.25	0.01
Kurtosis	−1.43	1.58	1.32	0.82	−0.97
Skewness	−0.41	−1.74	0.44	−1.44	0.00
Minimum	0.01	0.00	0.90	0.00	0.45
Maximum	0.02	18.32	0.96	49.10	0.72
Count	18	18	18	18	18

Variables	q (m²/s)	d₅₀ (mm)	h (m)	n (%)	OTE₂₀
	Training dataset
Mean	0.01	13.71	0.92	34.63	0.61
Median	0.01	15.59	0.92	40.88	0.62
Std. deviation	0.01	6.36	0.02	16.82	0.11
Variance	0.00	40.47	0.00	282.75	0.01
Kurtosis	−1.61	1.13	−0.51	0.49	0.08
Skewness	−0.11	−1.65	0.55	−1.37	−0.35
Minimum	0.01	0.00	0.90	0.00	0.34
Maximum	0.02	18.32	0.96	49.10	0.86
Count	42	42	42	42	42
	Test dataset
Mean	0.012	13.71	0.92	34.63	0.60
Median	0.01	15.59	0.92	40.88	0.58
Std. deviation	0.01	6.47	0.01	17.10	0.08
Variance	0.00	41.83	0.00	292.25	0.01
Kurtosis	−1.43	1.58	1.32	0.82	−0.97
Skewness	−0.41	−1.74	0.44	−1.44	0.00
Minimum	0.01	0.00	0.90	0.00	0.45
Maximum	0.02	18.32	0.96	49.10	0.72
Count	18	18	18	18	18

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