23
Views
3
CrossRef citations to date
0
Altmetric
Original Articles

Application of Fractional Order ABC and GA for Neural Network Training and Clustering Process

&
Pages 900-913 | Received 29 Jul 2014, Accepted 04 May 2015, Published online: 21 Sep 2015

References

  • P. Tsai, J. Pan, P. Shi and B. Liao, A New Framework for Optimization Based-On Hybrid Swarm Intelligence, Handbook of Swarm Intelligence (2011) vol. 8 421–449.
  • W. Deng, R. Chen, B. He, Y. Liu, L. Yin and J. Guo, A novel two-stage hybrid swarm intelligence optimization algorithm and application, Soft Computing (2012) vol. 6 1707–1722.
  • S. Kim, I. Kim, V. Mani, V and H.J. Kim, Ant Colony Optimization for SONET Ring Loading Problem, International Journal of Innovative Computing, Information and Control (2008) vol. 4 1617–1626.
  • S. Nakajima, H. Arimot, H. Rensha and T. Toriu, Measurement of a Translation and a Rotation of a Tooth after an Orthodontic Treatment Using GA, International Journal of Innovative Computing Information and Control (2007) vol. 3 no. 6 (A) 1399–1406.
  • A. George, B. Rajakumar, D. Binu, Genetic algorithm based airlines booking terminal open/close decision system, Proceedings of the International Conference on Advances in Computing, Communications and Informatics (2012) pp. 174–179.
  • M. Subotic, Artificial bee colony algorithm with multiple onlookers for constrained optimization problems, Proceedings of the 5th European conference on European computing conference (2011) pp. 251–256.
  • B. Rajakumar, The Lion's Algorithm: A New Nature Inspired Search Algorithm, Procedia Technology (2012) vol. 6C 126–135.
  • D. Martens, B. Baesens and T. Fawcett, Editorial survey: swarm intelligence for data mining, Journal Machine Learning archive (2011) vol. 82 no. 1 1–42.
  • T. Hashni and T. Amudha, Relative Study of CGS with ACO and BCO Swarm Intelligence Techniques, International Journal of Computer Technology &Applications (2012) vol. 3, no. 5 1775–1781.
  • A. Garg, P. Gill, P. Rathi, Amardeep and K. Garg, An Insight into Swarm Intelligence, International Journal of Recent Trends in Engineering (2009) vol. 2, no. 8 42–44.
  • M. Mahant., B. Choudhary, A. Kesharwani and K. Rathore, A Profound Survey on Swarm Intelligence, International Journal of Advanced Computer Research (2012) vol. 2 no. 1 31–36.
  • A. George A and B. Rajakumar, Fuzzy Aided Ant Colony Optimization Algorithm to Solve Optimization Problem, Advances in Intelligent Systems and Computing, Intelligent Informatics (2013) vol. 182 207–215.
  • S. Binitha and S. Sathya, A Survey of Bio inspired Optimization Algorithms, International Journal of Soft Computing and Engineering (2012) vol. 2 no. 2 137–151.
  • L. Castro, Fundamentals of natural computing: an overview, Physics Life Reviews (2007) vol. 4, no. 1 1–36.
  • X. Gao, S.J. Ovaska and X. Wang, A GA-based Negative Selection Algorithm, International Journal of Innovative Computing Information and Control (2008) vol. 4, no. 4 971–979.
  • J. Ruiz-Vanoye, O. Díaz-Parra, F. Cocón and A. Soto, Meta-Heuristics Algorithms based on the Grouping of Animals by Social Behavior for the Traveling Salesman Problem, International Journal of Combinatorial Optimization Problems and Informatics (2012) vol. 3 no. 3 104–123.
  • B. Shivakumar and T. Amudha, A Novel Nature-inspired Algorithm to solve Complex Generalized Assignment Problems, International Journal of Research and Innovation in Computer Engineering (2012) vol. 2 no. 3 280–284.
  • J. Holland, Adaptation in natural and artificial systems (University of Michigan Press Ann Arbor, Mich. 1975).
  • D. Goldberg, Genetic algorithms in search, optimization and machine Learning, (Addison-Wesley Publishing Co., Inc., Reading, Mass. 1989).
  • R. Sharapov, Genetic Algorithms: Basic Ideas, (Variants and Analysis, Vision Systems: Segmentation and Pattern Recognition, 2007).
  • T. Singh and Z.M. Sandhu, An Approach in the Software Testing Environment using Artificial Bee Colony (ABC) Optimization, International Journal of Computer Applications (0975 – 8887) (2012) vol. 58, no. 21.
  • E. Gerhardt E and H. Gomes, Artificial Bee Colony (ABC) Algorithm for Engineering Optimization Problems, 3rd International Conference on Engineering Optimization, (2012).
  • G. Lavanya and S. Srinivasan, FAGA: Hybridization of Fractional Order ABC and GA for Optimization”, International Arab Journal of Information Technology, Vol. 13, no.3. (Published Online)
  • J. Vesterstrom and R. Thomsen, A Comparative Study of Differential Evolution, Particle Swarm Optimization, and Evolutionary Algorithms on Numerical Benchmark Problems, Congress on Evolutionary Computation (2004) vol. 2 1980–1987.
  • J. Brest, S.W. Greiner, B. Boskovic, M. Mernik and V. Zumer, Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems, IEEE Transactions on Evolutionary Computation (2006) vol. 10 no. 6.
  • D. Karaboga and B. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, J Glob Optim (2007) vol. 39 459–471.
  • D. Anghinolfi and M. Paolucci, A new discrete particle swarm optimization approach for the single-machine total weighted tardiness scheduling problem with sequence-dependent setup times, European Journal of Operational Research (2009) vol. 193 no. 1 73–85.
  • M. Cheng and L. Lien, hybrid swarm intelligence based particle-bee algorithm for construction site layout optimization, Journal Expert Systems with Applications (2012) vol. 39 no. 10.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.