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New Trends in Fuzzy Clustering
Abstract
Fuzzy methodologies show progress day by day towards better explanation of various natural, social, engineering and information problem solutions in the best, economic, fast and effective manner. This chapter provides cluster analyses from probabilistic, statistical and especially fuzzy methodology points of view by consideration of various classical and innovative cluster modeling and inference systems. After the conceptual assessment explanation of fuzzy logic thinking fundamentals various clustering methodologies are presented with brief revisions but innovative trend analyses as k-mean-standard deviation, cluster regression, relative clustering for depiction of trend components that fall within different clusters. The application of fuzzy clustering methodology is presented for lake time series and earthquake modeling for rapid hazard assessment of existing buildings.
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