Predictive Power of Machine Learning for Optimizing Solar Water Heater Performance: The Potential Application of High-Throughput Screening

Table 1

Descriptive statistics of the variables for 915 samples of in service WGET-SWHs. Reproduced with permission from Liu et al. [2].

Items	Tube length (mm)	Number of tubes	TCD (mm)	Tank volume (kg)	Collector area (m^2)	Angle (°)	Final temp. (°C)	HCR
Maximum	2200	64	151	403	8.24	85	62	11.3
Minimum	1600	5	60	70	1.27	30	46	6.7
Data range	600	59	91	333	6.97	55	16	4.6
Average value	1811	21	76.2	172	2.69	46	53	8.9
Standard deviation	87.8	5.8	5.11	47.0	0.73	3.89	2.0	0.48

TCD: tube center distance; final temp.: final temperature; HCR: heat collection rate (MJ/m²). Tank volume was defined as the maximum mass of water in tank (kg).