Spatiotemporal Approaches for Quality Control and Error Correction of Atmospheric Data through Machine Learning

Table 5

Comparison of MLQC-NT results on raw data and interpolated data using SVR.

Weather element	Raw data					Interpolated data
	Correlation coefficient	RMSE	3σ error		Time (sec)	Correlation coefficient	RMSE	3σ error		Time (sec)
			#err/#total	Rateerr(%)				#err/#total	Rateerr(%)
Temperature	1.0000	0.0586	177/10050	1.76	1363	1.0000	0.0553	192/9665	1.99	1487
Humidity	0.9995	0.6424	504/10050	5.01	6881	0.9997	0.4690	185/6429	2.88	3298
UV-rays	0.9919	1.7307	4039/10050	40.19	5995	0.9919	1.7307	4039/10050	40.19	5995
PM2.5	0.9211	8.1466	382/10050	3.80	5400	0.9834	3.6097	372/10013	3.72	3044
Solar radiation	0.9388	0.0039	52/10050	0.52	3605	0.9388	0.0039	52/10050	0.52	3605
u	0.7592	0.5801	560/10050	5.57	1414	0.7772	0.3563	386/7254	5.32	543
	0.7650	0.7378	591/10050	5.88	1496	0.7848	0.4244	451/7254	6.22	580