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Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization
Joint Authors
Sheikh Abdullah, Siti Norul Huda
Othman, Zulaiha Ali
Abdulameer, Mohammed Hasan
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-25
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM.
However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution.
To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed.
To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM).
In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset.
In this method, we initially perform feature extraction and then recognition on the extracted features.
In the recognition process, the extracted features are used for SVM training and testing.
During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values.
The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition.
A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.
American Psychological Association (APA)
Abdulameer, Mohammed Hasan& Sheikh Abdullah, Siti Norul Huda& Othman, Zulaiha Ali. 2014. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1051265
Modern Language Association (MLA)
Abdulameer, Mohammed Hasan…[et al.]. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1051265
American Medical Association (AMA)
Abdulameer, Mohammed Hasan& Sheikh Abdullah, Siti Norul Huda& Othman, Zulaiha Ali. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1051265
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051265