Research Article
Regression Model to Predict Global Solar Irradiance in Malaysia
Table 6
Comparison of PM performance with existing global solar irradiance models.
| Number | Model | RMSE (%) | MBE (%) | |
| 1 | El-Metwally [10] | 6.000 | 0.1000 | NaN | 2 | Badescu [11] | 5.000 | 4.000 | NaN | 3 | Almorox et al. [12] | 2.141 | 0.1210 | 0.874 | 4 | Zhao et al. [7] | 1.960 | | 0.920 | 5 |
Liu and Scott [14] | 1.740 | NaN | 0.859 | 6 | Khorasanizadeh and Mohammadi [15] | NaN | NaN | 0.996 | 7 | Shavalipour et al. [16] | 5.203 | 0.4400 | NaN | 8 | Liu and Scott [14] | 1.740 | NaN | 0.818 | 9 | Masral et al. [18] | 2.418 | NaN | 0.966 | 10 |
Li et al. [22] | 1.647 | 1.286 | 0.929 | 11 | Pandey and Soupir [23] | 16.000 | 16.000 | 0.990 | 12 |
Vakili et al. [24] | 1.000 | NaN | 0.980 | 13 | Koca et al. [25] | 3.580 | NaN | 0.997 | 14 | Almorox et al. [26] | 2.709 | | 0.895 | 15 | Polo [27] | 11.100 | | NaN | 16 | PM1 | 1.774 | 0.3540 | 0.950 | 17 | PM2 | 0.699 | | 0.992 | 18 | PM3 | 1.057 | | 0.982 | 19 | PM4 | 0.421 | 0.0001 | 0.997 | 20 | PM5 | 1.912 | 0.1089 | 0.942 | 21 | PM6 | 0.839 | 0.3620 | 0.989 | 22 | PM7 | 0.972 | | 0.985 | 23 | PM8 | 1.743 | 0.6025 | 0.952 | 24 | PM9 | 1.549 | 0.3090 | 0.962 | 25 | PM10 | 1.213 | 0.2679 | 0.977 | 26 | PM11 | 2.0228 | 0.4691 | 0.9354 | 27 | PM12 | 0.8561 | 0.2822 | 0.9884 |
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