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In this paper an idea for classification of energy consumption profiles using an evolving c-regression method is presented. Cluster prototypes (centers) are usually defined as a mean of data around the center. The cluster center is a vector of numerical values. The method presented in this paper uses Takagi-Sugeno fuzzy models as a cluster prototype. Beside the method description also preliminary...
This paper presents an idea of evolving Gustafson-Kessel possibilistic c-means clustering (eGKPCM). This approach is extension of well known possiblilistic c-means clustering (PCM) which was proposed to address the drawbacks associated with the constrained membership functions used in fuzzy c-means algorithms (FCM). The idea of possiblistic clustering is ap- pealing when the data samples are highly...
In this paper a new approach to data stream evolving fuzzy model identification is given. The structure of the model is given in the form of Takagi-Sugeno and the partitioning of the input-output space is obtained using a fuzzy c-regression clustering method and the approach also involves the evolving properties. The method is given in a recursive form. The proposed approach is shown with two simple...
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