Underground water level dynamic prediction based on hybrid genetic algorithm and the least square support vector model

This paper will be least square support vector machine applied in underground water level forecasting calculation, based on rainfall, and the time is a ground water level of the underground water level for input combination forecast model, model of the super parameter the hybrid genetic algorithm was used to optimize the determined, the combination of Wanjiazhai Yellow River water supply area in Taiyuan measured data for the underground water level for verification. The results show that prediction model of underground water level has a high precision, and can be used to predict the region of underground water level.