Air quality forecasting is closely related to people's daily life. At present, the WRF-CMAQ simulation system is commonly used to forecast air quality. However, due to the uncertainty of the simulated weather field and the emission inventory, the results of the WRF-CMAQ forecast model are not ideal. In order to solve the above problems, this paper proposes an air quality prediction model based on Genetic Algorithm (GA) to optimize the parameters of Weighted Extreme Learning Machine (WELM). The experimental results show that the new GA-WELM model has good generalization ability and effectively improves the forecast accuracy
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