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logic fabric of structure in a data set by describing it in the form of a union of clusters (that is fuzzy relations) determined by the clustering algorithm. In contrast to the standard FCM, the elements (clusters) are combined together as a union of such fuzzy relations. Both clusters and this for
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https://doi.org/10.1057/9780230590687omprehensible, reflect the experimental evidence and have a stable interpretation as entities that bridge experimental reality with the subjective and ultimately observer-based judgement about the environment. Once being semantically stable, information granules could be viewed as architecture-indep
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Melancholy Science as Dissonant System,n was accomplished in the framework of fuzzy sets by being directly associated with the granular descriptors realized in the form of fuzzy clusters (fuzzy relations). In the proposed mechanisms of collaboration, we have made two assumptions that were consistently kept throughout the entire flow of i
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Granular Computing978-1-4615-1033-8Series ISSN 0893-3405
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https://doi.org/10.1007/978-3-031-24494-0nteractions arising between them. The first trend is motivated by the complexity and diversity of the granular aspect of information. The second category of developments is motivated by a multifaceted nature of information granularity that usually embraces several dimensions of such concept.
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