Showing results for: real-time water analyzer Articles
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Comparison of random forests and other statistical methods for the prediction of lake water level: a case study of the Poyang Lake in China
Modeling of hydrological time series is essential for sustainable development and management of lake water resources. This study aims to develop an efficient model for forecasting lake water level variations, exemplified by the Poyang Lake (China) case study. A random forests (RF) model was first applied and compared with artificial neural networks, support vector regression, and a linear ...
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