Prediction of Pan Evaporation Based on KNN-TCN Model
Accurate prediction of evaporation is of great significance for the rational development and utilization of water resources,the study of drought and flood trends,and the estimation of crop irrigation water consumption.In this paper,7 meteorological data observed by 14 ground international exchange stations in northern China were selected.Based on the time convolution network(TCN)model,the K-nearest neighbor(KNN)algorithm was used to screen the spatial factors of pan evaporation.The KNN-TCN pan evaporation prediction model was built and the average absolute error,root mean square error and coefficient of determination were used to evaluate the evaporation prediction ac-curacy of the target site.The results show that a)the prediction results of KNN-TCN model are significantly better than that of LSTM model.b)Compared with the basic TCN model,the determination coefficient of KNN-TCN model is increased by 2.52%,and the mean absolute error and root mean square error are reduced by 23.97%and 13.06%,respectively.
evaporation capacity of evaporating dishtime convolution networkK-nearest neighbor algorithmspatial factors
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