Comparison of three machine learning models in dynamic simulation of groundwater level
In order to simulate the dynamic change of regional groundwater level,three machine learning models including Extreme Learning Machine(ELM),Nonlinear Auto-Regressive models with exogenous inputs(NARX)and Random Forest(RF)based on parameter subset selecting and training were established to simulate the dynamic change of groundwater level in Mi-huai-shun region.The comparison of the accuracy of the three machine learning models showed that RF model＞NARX model＞ELM model.Compared with ELM model,NARX model and RF model were more suitable for the simulation of groundwater level in Mi-huai-shun region.Additionally,the dynamic change modes of groundwater table in different monitoring wells were classified into two types:wavelike and steady rising.The NARX model was more suitable for simulating the wavelike rising of the groundwater level,while RF model was more suitable for simulating the steady rising of the groundwater level.The results of this study provide methodological reference for the application of machine learning model in groundwater level analysis.
machine learning modelsdynamic simulation of groundwater levelmodel comparison
万方数据
维普
