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- W2915468460 abstract "This work focuses on models selection in a multi-model air quality ensemble system. The models are operational long-range transport and dispersion models used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides in the atmosphere. In this context, a methodology based on temporal hierarchical agglomeration is introduced. It uses fuzzy similarity relations combined by a transitive consensus matrix. The methodology is adopted for individuating a subset of models that best characterize the predicted atmospheric pollutants from the ETEX-1 experiment and discard redundant information." @default.
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- W2915468460 date "2019-01-01" @default.
- W2915468460 modified "2023-09-27" @default.
- W2915468460 title "Fuzzy Similarity-Based Hierarchical Clustering for Atmospheric Pollutants Prediction" @default.
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- W2915468460 doi "https://doi.org/10.1007/978-3-030-12544-8_10" @default.
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