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• W2535646075 abstract "This paper proposes an online evolving fuzzy clustering algorithm based on maximum likelihood estimator. In this methodology, the distance from a point to center of the cluster is computed by maximum likelihood similarity of data. The mathematical formulation is developed from the Takagi-Sugeno (TS) fuzzy inference system. The performance and application of the proposed methodology is based on prediction of the Box-Jenkins (Gas Furnace) time series. Computational results of a comparative analysis with other methods widely cited in the literature illustrates the effectiveness of the proposed methodology." @default.
• W2535646075 created "2016-10-28" @default.
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• W2535646075 date "2014-12-01" @default.
• W2535646075 modified "2023-09-25" @default.
• W2535646075 title "Evolving maximum likelihood clustering algorithm" @default.
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• W2535646075 doi "https://doi.org/10.1109/eals.2014.7009511" @default.
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