Post-processing of hydrological model simulations using the convolutional neural network and support vector regression
Post-processing methods can be used to reduce the biases of hydrological models. In this research, six post-processing methods are compared: quantile mapping (QM) methods, which include four kinds of transformations, and two newly established machine learning frameworks [support vector regression (S...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IWA Publishing
2022-04-01
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| Series: | Hydrology Research |
| Subjects: | |
| Online Access: | http://hr.iwaponline.com/content/53/4/605 |