A New Binary Adaptive Elitist Differential Evolution Based Automatic k-Medoids Clustering for Probability Density Functions
Joint Authors
Pham-Toan, D.
Vo-Van, T.
Pham-Chau, A. T.
Nguyen-Trang, T.
Ho-Kieu, D.
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-22
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
This paper proposes an evolutionary computing based automatic partitioned clustering of probability density function, the so-called binary adaptive elitist differential evolution for clustering of probability density functions (baeDE-CDFs).
Herein, the k-medoids based representative probability density functions (PDFs) are preferred to the k-means one for their capability of avoiding outlier effectively.
Moreover, addressing clustering problem in favor of an evolutionary optimization one permits determining number of clusters “on the run”.
Notably, the application of adaptive elitist differential evolution (aeDE) algorithm with binary chromosome representation not only decreases the computational burden remarkably, but also increases the quality of solution significantly.
Multiple numerical examples are designed and examined to verify the proposed algorithm’s performance, and the numerical results are evaluated using numerous criteria to give a comprehensive conclusion.
After some comparisons with other algorithms in the literature, it is worth noticing that the proposed algorithm reveals an outstanding performance in both quality of solution and computational time in a statistically significant way.
American Psychological Association (APA)
Pham-Toan, D.& Vo-Van, T.& Pham-Chau, A. T.& Nguyen-Trang, T.& Ho-Kieu, D.. 2019. A New Binary Adaptive Elitist Differential Evolution Based Automatic k-Medoids Clustering for Probability Density Functions. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1196516
Modern Language Association (MLA)
Pham-Toan, D.…[et al.]. A New Binary Adaptive Elitist Differential Evolution Based Automatic k-Medoids Clustering for Probability Density Functions. Mathematical Problems in Engineering No. 2019 (2019), pp.1-16.
https://search.emarefa.net/detail/BIM-1196516
American Medical Association (AMA)
Pham-Toan, D.& Vo-Van, T.& Pham-Chau, A. T.& Nguyen-Trang, T.& Ho-Kieu, D.. A New Binary Adaptive Elitist Differential Evolution Based Automatic k-Medoids Clustering for Probability Density Functions. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1196516
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196516