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The search capability of GWA is used to search the optimal cluster centers in the given feature space. The agent representation is used to encode the centers of clusters. The proposed GWAC technique is tested on both artificial and real-life data sets and compared to six well-known metaheuristic-based clustering techniques. The computational results are encouraging and demonstrate that GWAC provides better values in terms of precision, recall, G-measure, and intracluster distances. GWAC is further applied for gene expression data set and its performance is compared to other techniques. Experimental results reveal the efficiency of the GWAC over other techniques.<\/jats:p>","DOI":"10.1515\/jisys-2014-0137","type":"journal-article","created":{"date-parts":[[2016,2,4]],"date-time":"2016-02-04T05:35:46Z","timestamp":1454564146000},"page":"153-168","source":"Crossref","is-referenced-by-count":39,"title":["Grey Wolf Algorithm-Based Clustering Technique"],"prefix":"10.1515","volume":"26","author":[{"given":"Vijay","family":"Kumar","sequence":"first","affiliation":[{"name":"Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India"}]},{"given":"Jitender Kumar","family":"Chhabra","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, National Institute of Technology, Kurukshetra, Haryana, India"}]},{"given":"Dinesh","family":"Kumar","sequence":"additional","affiliation":[{"name":"Computer Science and Engineering Department, GJUS and T, Hisar, Haryana, India"}]}],"member":"374","published-online":{"date-parts":[[2016,2,4]]},"reference":[{"key":"2025120523260705209_j_jisys-2014-0137_ref_001_w2aab3b7c25b1b6b1ab2ab1Aa","unstructured":"B. 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