Drought driving mechanism and risk situation prediction based on machine learning models in the Yellow River Basin, China
Author:
Affiliation:
1. School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan, China
Funder
National Key R&D Program of China
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://www.tandfonline.com/doi/pdf/10.1080/19475705.2023.2279493
Reference71 articles.
1. Effect of Gradient Descent Optimizers and Dropout Technique on Deep Learning LSTM Performance in Rainfall-runoff Modeling
2. Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models
3. Drought indicator analysis and forecasting using data driven models: case study in Jaisalmer, India
4. Combination of Limited Meteorological Data for Predicting Reference Crop Evapotranspiration Using Artificial Neural Network Method
5. Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models
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