一种融合时空特性的气温缺失记录重建方法
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陈锋锐, 刘宇, 李熙
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A Novel Imputation Method of Missing Air Temperature Records Based on Merging Spatio-temporal Characteristics
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Feng-rui CHEN, Yu LIU, Xi LI
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表3 4种方法对月平均气温的重建精度(0.1℃) |
Table 3 The accuracy for the imputed monthly averageair air temperature records by four methods (0.1℃) |
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月份(月) | 线性插值 | OKD | NR | 提出方法 | MAE | RMSE | MAE | RMSE | MAE | RMSE | MAE | RMSE | 1 | 10.2 | 10.9 | 7.5 | 10.3 | 15.4 | 17.9 | 2.3a | 3.2 b | 2 | 35.2 | 35.9 | 6.3 | 9.9 | 20 | 41 | 2.9 a | 4.1 b | 3 | 11.1 | 11.8 | 7.3 | 10.9 | 8.2 | 15.8 | 1.6 a | 2.1b | 4 | 11.2 | 12.2 | 8.1 | 11.2 | 2.0 | 2.6 | 1.9 a | 2.4 b | 5 | 4.5 | 5.7 | 7.0 | 10.0 | 2.0 | 2.6 | 1.8 a | 2.4 b | 6 | 13.1 | 13.9 | 7.4 | 10.5 | 2.2 | 2.9 | 1.8 a | 2.3 b | 7 | 7.1 | 8.7 | 6.4 | 9.3 | 1.9 a | 2.5 b | 1.9 a | 2.5 b | 8 | 7.1 | 9.3 | 5.6 | 8.1 | 2.1 | 2.7 | 1.9 a | 2.5 b | 9 | 6.4 | 8.1 | 6.0 | 8.5 | 2.1 | 2.8 | 1.8 a | 2.3 b | 10 | 5.1 | 5.7 | 6.7 | 8.4 | 1.8 | 2.4 | 1.6 a | 2.1 b | 11 | 10.9 | 11.9 | 7.5 | 9.4 | 4.4 | 7.5 | 2.5 a | 3.4 b | 12 | 17.9 | 19.6 | 7.2 | 9.2 | 41.7 | 81.9 | 2.6 a | 3.6b | 平均 | 11.6 | 12.8 | 6.9 | 9.6 | 8.7 | 15.4 | 2.1 a | 2.7 b |
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