Ies are processed. Six inducing points are applied to both FITC and VFE. Experiment 2:

Ies are processed. Six inducing points are applied to both FITC and VFE. Experiment 2: Impacts of s f on prediction accuracy and uncertainty. l is set for the 2 optimised value. s f varies from 0.1 by way of to 30.0. n is set to 0.5 and 1.five, respectively. NO data from each cities are processed. Six inducing points are applied to each FITC and VFE. Experiment three: Impacts of l on prediction accuracy and uncertainty. s f is set towards the 2 optimised worth. l varies from 0.1 by way of to 30.0. n is set to 0.5 and 1.five, respectively. NO data from both cities are processed. Six inducing points are applied to both FITC and VFE.RMSE =iNum (yi – yi )2 =1 , Num(34)exactly where yi could be the ground truth value and yi represents predicted meant. Num will be the sample number in testing set. Figures five and 6 show the results from Experiment 1. To make the outcomes more 2 distinguishable, the horizontal axes on the figures are set to log(n ). We can see from two is compact, GPs execute the most beneficial normally, when the efficiency Figure five that when n 2 of FITC and VFE varies. We are able to also observe that as n keeps escalating, the RMSE becomes incredibly important for all methods/pollutants. Related benefits may be observed from Figure six also. Both comply with our theoretical conclusions, despite the truth that the 2 Neumann series is used to approximate the matrix inverse. We also notice that n includes a 2 ) reaches much more important effect on Sheffield information as RMSE increases ealier right after log(nAtmosphere 2021, 12,11 ofzero. From Figure 6b,c, we also see that the uncertainty bounds of Sheffield information are 2 higher just after log(n ) reaches zero. We feel the explanation is the fact that Sheffield information are usually significantly less periodical than Pershawar information (see Figure two), which influences the performance of the models.Pesh-NO-GP Pesh-NO-VFE Pesh-NO-FITC VU0359595 Technical Information Shef-NO-GP Shef-NO-VFE Shef-NO-FITCPesh-NO -GPPesh-NO two -VFE2.two.Pesh-NO -FITCShef-NO2 -GP Shef-NO -VFEShef-NO2 -FITC1.1.0.0.—-(a)3Pesh-SO -GP2 2(b)Pesh-PM2.five 2.five two.-GP -VFE -FITCPesh-SO -VFE2.Pesh-SO -FITC Shef-SO -GP2 22.Pesh-PM Pesh-PM Shef-PMShef-SO -VFE2.5 2.5 two.-GP -VFE -FITCShef-SO -FITCShef-PM Shef-PM1.1.0.0.—-(c)(d)two Figure five. Relationship of n with 4 pollutants prediction RMSE: (a) NO, (b) NO2 , (c) SO2 , (d) PM2.five .8 six four 2 0 -2 -2 -1 0 1 2 3Pesh_NO_GP Pesh_NO_VFE Pesh_NO_FITC Shef_NO_GP Shef_NO_VFE Shef_NO_FITC8 7 6 5 4 3 two 1 0 -1 -2 -2 -1 0 1 two 3Pesh-NO 2 -GP Pesh-NO two -VFE Pesh-NO two -FITC Shef-NO2 -GP Shef-NO2 -VFE Shef-NO2 -FITC(a)eight 7 6 5 4 4 3Pesh-SO2 -GP(b)eight 7 6Pesh-PM two.five -GP Pesh-PM 2.5 -VFE Pesh-PM 2.five -FITC Shef-PM 2.5 -GP Shef-PM 2.five -VFE Shef-PM 2.5 -FITCPesh-SO2 -VFE Pesh-SO2 -FITC Shef-SO 2 -GP Shef-SO two -VFE Shef-SO 2 -FITC1 0 -1 -2 -2 -1 0 12 1 0 -1 four -2 -1 0 1 two 3(c)(d)two Figure 6. Connection of n with pollutants prediction uncertainty bound: (a) NO, (b) NO2 , (c) SO2 , (d) PM2.5 .Atmosphere 2021, 12,12 of4.three. Impacts of Noise Level on ELBO and UBML Figure 7 shows the results from Experiment 2. Pristinamycine medchemexpress According to our theoretical outcomes, the influence of s f around the uncertainty ought to develop into higher as s f increases. This can be verified by the outcomes shown in Figure 7b,d. Our theoretical results also suggest that the variation of s f wouldn’t have an effect on the prediction accuracy. We are able to see from Figure 7a,c that when s f is smaller, it does affect the prediction accuracy, but when it exceeds a particular worth, the impacts turn out to be negligible. Taking into consideration the Neumann series approximation, we would say that the experimental benefits comply together with the theoretical.