An Improved Clustering Algorithm Using Fuzzy Relation for the Performance Evaluation of Humanistic Systems

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dc.contributor.authorIsmat Beg
dc.contributor.authorTabasam Rashid
dc.date.accessioned2015-03-05T13:01:50Z
dc.date.available2015-03-05T13:01:50Z
dc.date.issued2014
dc.description.abstractA hierarchical structure is proposed for the performance evaluation of vague, complicated humanistic systems. An improved fuzzy clustering algorithm is developed to produce several partition trees with different levels and clusters according to different triangular norm compositions. Additionally, a fuzzy clustering algorithm is given to produce a partition tree without using the transitive closure composition. The usefulness of the proposed algorithm is illustrated by an example of actual academic data. C _ 2014 Wiley Periodicals, Inc.en_US
dc.identifier.citation24. Beg, I., & Rashid, T. (2014). An Improved Clustering Algorithm Using Fuzzy Relation for the Performance Evaluation of Humanistic Systems. International Journal of Intelligent Systems, 29(12), 1181-1199.en_US
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/1423
dc.language.isoenen_US
dc.publisherInternational Journal of Intelligent Systemsen_US
dc.titleAn Improved Clustering Algorithm Using Fuzzy Relation for the Performance Evaluation of Humanistic Systemsen_US
dc.typeArticleen_US
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