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- W2970713773 abstract "This study aims to develop a novel hybrid scheme of Artificial Neural Networks (ARN) coupled to a non-linear Kalman filterfor air quality forecasting in Guadalajara Metropolitan Area, in Mexico. ARN’s are widely used for air quality forecasting,however these schemes need large amounts of data regarding the pollutants concentration levels and meteorological data inorder to manage reliable forecasting. To address this issue, we present a scheme consisting of Neural Network modelsassisted by nonlinear Kalman filter that manage to considerably improve the forecasting performance, adding robustness incase of lack of data, and reducing the need of retraining over time." @default.
- W2970713773 created "2019-09-05" @default.
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- W2970713773 date "2018-03-01" @default.
- W2970713773 modified "2023-09-26" @default.
- W2970713773 title "Hybrid Artificial Neural Network Coupled with Kalman Filters for Air Quality Forecasting in Guadalajara, Mexico" @default.
- W2970713773 hasPublicationYear "2018" @default.
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