References

Abdulameer, M.H., D. Mohammed, S.A. Mohammed, M. Al-Azawi and Y.M.H. Al-Mayali et al., 2018. Face recognition technique based on Adaptive Opposition Particle Swarm Optimization (AOPSO) and Support Vector Machine (SVM). ARPN. J. Eng. Appl. Sci., 13: 2259-2266.

Abdulameer, M.H., S.N.H.S. Abdullah and Z.A. Othman, 2014. Support vector machine based on adaptive acceleration particle swarm optimization. Sci. World J. 10.1155/2014/835607

Africa, A.D.M., 2017. A particle swarm optimization conflict resolution model for computer network diagnostics. J. Eng. Appl. Sci., 12: 4330-4333.
Direct Link  |  

Aitkenhead, M.J. and A.J.S. McDonald, 2003. A neural network face recognition system. Eng. Appl. Artif. Intell., 16: 167-176.
Direct Link  |  

Anonymous, 2007. CASIA face database. Chinese Academy of Sciences, Beijing, China.

Gao, Y.L., X.H. An and J.M. Liu, 2008. A particle swarm optimization algorithm with logarithm decreasing inertia weight and chaos mutation. Proceedings of the 2008 International Conference on Computational Intelligence and Security (CIS'08) Vol. 1, December 13-17, 2008, IEEE, Suzhou, China, ISBN:978-0-7695-3508-1, pp: 61-65.

Gold, C. and P. Sollich, 2003. Model selection for support vector machine classification. Neurocomputing, 55: 221-249.
Direct Link  |  

Hasan, M., S.N.H.S. Abdullah and Z.A. Othman, 2013. Face recognition based on opposition particle swarm optimization and support vector machine. Proceedings of the 2013 IEEE International Conference on Signal and Image Processing Applications (ICSIPA’13), October 8-10, 2013, IEEE, Melaka, Malaysia, ISBN:978-1-4799-0267-5, pp: 417-424.

Jabeen, R., A. Ahmad and M. Iqbal, 2009. Phytoremediation of heavy metals: Physiological and molecular mechanisms. Bot. Rev., 75: 339-364.
CrossRef  |  Direct Link  |  

Kalivarapu, V., J.L. Foo and E. Winer, 2009. Synchronous parallelization of particle swarm optimization with digital pheromones. Adv. Eng. Software, 40: 975-985.
CrossRef  |  Direct Link  |  

Lauer, F. and G. Bloch, 2008. Incorporating prior knowledge in support vector machines for classification: A review. Neurocomputing, 71: 1578-1594.
CrossRef  |  Direct Link  |  

Shailaja, K. and B. Anuradha, 2017. Improved face recognition using a modified PSO based self-weighted linear collaborative discriminant regression classification. J. Eng. Appli. Sci., 12: 7234-7241.
CrossRef  |  Direct Link  |  

Sun, T.H. and F.C. Tien, 2008. Using backpropagation neural network for face recognition with 2D+3D hybrid information. Expert Syst. Appl., 35: 361-372.
CrossRef  |  Direct Link  |  

Wei, J., Z, Jian-Qi and Z. Xiang, 2011. Face recognition method based on support vector machine and particle swarm optimization. Expert Syst. Appl., 38: 4390-4393.
CrossRef  |  Direct Link  |  

Yang, X.S., S. Deb and S. Fong, 2011. Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications. In: Networked Digital Technologies, Fong, S. (Ed.). Springer, Berlin, Germany, ISBN:978-3-642-22184-2, pp: 53-66.