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Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-11-02
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
One heuristic evolutionary algorithm recently proposed is the grey wolf optimizer (GWO), inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature.
This paper presents an extended GWO algorithm based on Powell local optimization method, and we call it PGWO.
PGWO algorithm significantly improves the original GWO in solving complex optimization problems.
Clustering is a popular data analysis and data mining technique.
Hence, the PGWO could be applied in solving clustering problems.
In this study, first the PGWO algorithm is tested on seven benchmark functions.
Second, the PGWO algorithm is used for data clustering on nine data sets.
Compared to other state-of-the-art evolutionary algorithms, the results of benchmark and data clustering demonstrate the superior performance of PGWO algorithm.
American Psychological Association (APA)
Zhang, Sen& Zhou, Yongquan. 2015. Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis. Discrete Dynamics in Nature and Society،Vol. 2015, no. 2015, pp.1-17.
https://search.emarefa.net/detail/BIM-1060526
Modern Language Association (MLA)
Zhang, Sen& Zhou, Yongquan. Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis. Discrete Dynamics in Nature and Society No. 2015 (2015), pp.1-17.
https://search.emarefa.net/detail/BIM-1060526
American Medical Association (AMA)
Zhang, Sen& Zhou, Yongquan. Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis. Discrete Dynamics in Nature and Society. 2015. Vol. 2015, no. 2015, pp.1-17.
https://search.emarefa.net/detail/BIM-1060526
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1060526