Clustering and visualization approaches for human cell cycle gene expression data analysis
International Journal of Approximate Reasoning
A novel hierarchical-clustering-combination scheme based on fuzzy-similarity relations
IEEE Transactions on Fuzzy Systems
Fast window fusion using fuzzy equivalence relation
Pattern Recognition Letters
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Aim of this work is to introduce a methodology, based on the combination of multiple temporal hierarchical agglomerations, for model comparisons in a multi-model ensemble context. We take advantage of a mechanism in which hierarchical agglomerations can easily combined by using a transitive consensus matrix. The hierarchical agglomerations make use of fuzzy similarity relations based on a generalized Łukasiewicz structure. The methodology is adopted to analyze data from a multimodel air quality ensemble system. The models are operational longrange transport and dispersion models used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides in the atmosphere. We apply the described methodology to agglomerate and to individuate the models that characterize the predicted atmospheric pollutants from the ETEX-1 experiment.