Data Clustering Using Moth-Flame Optimization Algorithm
Data Clustering Using Moth-Flame Optimization Algorithm
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers. Besides, due to weak exploration capability, it is easily stuck at local optima. Recently, a new metaheuristic called Moth Flame Optimizer (MFO) is proposed to handle comple...
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Data Clustering Using Moth-Flame Optimization Algorithm
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TN_cdi_doaj_primary_oai_doaj_org_article_bb3fd51af86e4c3e92b5d4f645ff51ee
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bb3fd51af86e4c3e92b5d4f645ff51ee
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ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s21124086
