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Outline
In order to improve the accuracy of runoff prediction, based on the control variable method and the daily runoff data of Lanzhou hydrometric station from August 2001 to December 2019, the models of the LSTM, ARIMA, SVR and XGBoost were used to establish 12 model schemes, including single model, EMD decomposition and reconstruction, EMD decomposition and reconstruction after removing noise components, and evaluation indicators of the 12 schemes were compared. The results show that the EMD sequence decomposition and reconstruction technology and noise component elimination based on Hurst exponent are helpful to improve the prediction accuracy. Compared with the single model, the RRMSE of the model constructed by the former decreased by 15.16% on average, and that of the latter decreased by 28.49% on average. Among the 12 schemes, EMD-SVR-ARIMA with noise components removed is the best model.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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