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New Trends in Fuzzy Clustering

New Trends in Fuzzy Clustering

Zekâi Sen
Copyright: © 2013 |Pages: 41
ISBN13: 9781466642133|ISBN10: 1466642130|EISBN13: 9781466642140
DOI: 10.4018/978-1-4666-4213-3.ch012
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MLA

Sen, Zekâi. "New Trends in Fuzzy Clustering." Data Mining in Dynamic Social Networks and Fuzzy Systems, edited by Vishal Bhatnagar, IGI Global, 2013, pp. 248-288. https://doi.org/10.4018/978-1-4666-4213-3.ch012

APA

Sen, Z. (2013). New Trends in Fuzzy Clustering. In V. Bhatnagar (Ed.), Data Mining in Dynamic Social Networks and Fuzzy Systems (pp. 248-288). IGI Global. https://doi.org/10.4018/978-1-4666-4213-3.ch012

Chicago

Sen, Zekâi. "New Trends in Fuzzy Clustering." In Data Mining in Dynamic Social Networks and Fuzzy Systems, edited by Vishal Bhatnagar, 248-288. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-4213-3.ch012

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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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