CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Yagi-Uda Antenna Design Optimization for Maximum Gain using different BBO Migration Variants

by Satvir Singh, Gagan Sachdeva
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 5
Year of Publication: 2012
Authors: Satvir Singh, Gagan Sachdeva
10.5120/9278-3471

Satvir Singh, Gagan Sachdeva . Yagi-Uda Antenna Design Optimization for Maximum Gain using different BBO Migration Variants. International Journal of Computer Applications. 58, 5 ( November 2012), 14-18. DOI=10.5120/9278-3471

@article{ 10.5120/9278-3471,
author = { Satvir Singh, Gagan Sachdeva },
title = { Yagi-Uda Antenna Design Optimization for Maximum Gain using different BBO Migration Variants },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 5 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 14-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number5/9278-3471/ },
doi = { 10.5120/9278-3471 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:01:40.061441+05:30
%A Satvir Singh
%A Gagan Sachdeva
%T Yagi-Uda Antenna Design Optimization for Maximum Gain using different BBO Migration Variants
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 5
%P 14-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biogeography is the study of distribution of biological species, over space and time, among random habitats. Recently developed Biogeography-Based Optimization (BBO) is a technique, where solutions of the problem under consideration are named as habitats; similar to chromosome in Genetic Algorithms (GAs) and particles in Particle Swarm Optimization (PSO). Feature sharing among various habitats, i. e. , exploitation, is made to occur due to migration operator wheras exploration of new SIV values, similar to that of GAs, is accomplished with mutation operator. In this paper, various migration variants of BBO algorithm, reported till date, are investigated to optimize the lengths and spacings for Yagi- Uda antenna elements for maximum gain. The results obtained with these migration variants are compared and the best results are presented in the ending sections of the paper.

References
  1. E. E. Altshuler and D. S. Linden. Wire-antenna Designs using Genetic Algorithms. Antennas and Propagation Magazine, IEEE, 39(2):33–43, 1997.
  2. S. Baskar, A. Alphones, P N Suganthan, and J J Liang. Design of Yagi-Uda Antennas using Comprehensive Learn-ing Particle Swarm Optimisation. IEEE, 152(5):340–346, 2005.
  3. JH Bojsen, H. Schjaer-Jacobsen, E. Nilsson, and J. Bach Andersen. Maximum Gain of Yagi–Uda Arrays. Electronics Letters, 7(18):531–532, 1971.
  4. G. J. Burke and A. J. Poggio. Numerical Electromagnetics Code (NEC) method of moments. NOSC Tech. DocLawrence Livermore National Laboratory, Livermore, Calif, USA, 116:1–131, 1981.
  5. C. Chen and D. Cheng. Optimum Element Lengths for Yagi-Uda Arrays. IEEE Transactions on Antennas and Propagation,, 23(1):8–15, 1975.
  6. D. Cheng and C. Chen. Optimum Element Spacings for Yagi-Uda Arrays. IEEE Transactions on Antennas and Propagation,, 21(5):615–623, 1973.
  7. D. K. Cheng. Optimization Techniques for Antenna Arrays. Proceedings of the IEEE, 59(12):1664–1674, 1971.
  8. D. K. Cheng. Gain Optimization for Yagi-Uda Arrays. Antennas and Propagation Magazine, IEEE, 33(3):42–46, 1991.
  9. D. Correia, A. J. M. Soares, and M. A. B. Terada. Optimization of gain, impedance and bandwidth in Yagi-Uda Antennas using Genetic Algorithm. IEEE, 1:41–44, 1999.
  10. D. Du, D. Simon, and M. Ergezer. Biogeography-based Optimization Combined with Evolutionary Strategy and Immigration Refusal. IEEE, 1:997–1002, 2009.
  11. H. Ehrenspeck and H. Poehler. A New Method for Obtaining Maximum Gain from Yagi Antennas. IRE Transactions on Antennas and Propagation,, 7(4):379–386, 1959.
  12. R. M. Fishenden and E. R. Wiblin. Design of Yagi Aerials. Proceedings of the IEE-Part III: Radio and Communication Engineering, 96(39):5, 1949.
  13. E. A. Jones andW. T. Joines. Design of Yagi-Uda Antennas using Genetic Algorithms. IEEE Transactions on Antennas and Propagation,, 45(9):1386–1392, 1997.
  14. Y. Kuwahara. Multiobjective Optimization Design of Yagi- Uda Antenna. IEEE Transactions on Antennas and Propagation,, 53(6):1984–1992, 2005.
  15. J. Y. Li. Optimizing Design of Antenna using Differential Evolution. IEEE, 1:1–4, 2007.
  16. H. Ma and D. Simon. Blended Biogeography-based Optimization for Constrained Optimization. Engineering Applications of Artificial Intelligence, 24(3):517–525, 2011.
  17. R. H. MacArthur and E. O. Wilson. The Theory of Island Biogeography. Princeton Univ Pr, 1967.
  18. T. McTavish and D. Restrepo. Evolving Solutions: The Genetic Algorithm and Evolution Strategies for Finding Optimal Parameters. Applications of Computational Intelligence in Biology, 1:55–78, 2008.
  19. S. S. Pattnaik, M. R. Lohokare, and S. Devi. Enhanced Biogeography-Based Optimization using Modified Clear Duplicate Operator. IEEE, 1:715–720, 2010.
  20. M. Rattan, M. S. Patterh, and B. S. Sohi. Optimization of Yagi-Uda Antenna using Simulated Annealing. Journal of Electromagnetic Waves and Applications, 22, 2(3):291– 299, 2008.
  21. D. G. Reid. The Gain of an Idealized Yagi Array. Journal of the Institution of Electrical Engineers-Part IIIA: Radiolocation,, 93(3):564–566, 1946.
  22. L. C. Shen. Directivity and Bandwidth of Single-band and Double-band Yagi Arrays. IEEE Transactions on Antennas and Propagation,, 20(6):778–780, 1972.
  23. D. Simon. Biogeography-based Optimization. IEEE Transactions on Evolutionary Computation,, 12(6):702–713, 2008.
  24. Satvir Singh, Eitika Mittal, and Gagan Sachdeva. Multi- Objective Gain-Impedance Optimization of Yagi-Uda Antenna using NSBBO and NSPSO. International Journal of Computer Applications, 56(15):1–6, 2012.
  25. Satvir Singh and Gagan Sachdeva. Mutation Effects on BBO Evolution in Optimizing Yagi-Uda Antenna Design. In proceeding of IEEE, 2012.
  26. U. Singh, H. Kumar, and T. S. Kamal. Design of Yagi-Uda Antenna Using Biogeography Based Optimization. IEEE Transactions on Antennas and Propagation,, 58(10):3375– 3379, 2010.
  27. U. Singh, M. Rattan, N. Singh, and M. S. Patterh. Design of a Yagi-Uda Antenna by Simulated Annealing for Gain, Impedance and FBR. IEEE, 1:974–979, 2007.
  28. Shintaro Uda and Yasuto Mushiake. Yagi-Uda Antenna. Maruzen Company, Ltd, 1954.
  29. N. V. Venkatarayalu and T. Ray. Single and Multi-Objective Design of Yagi-Uda Antennas using Computational Intelligence. IEEE, 2:1237–1242, 2003.
  30. N. V. Venkatarayalu and T. Ray. Optimum Design of Yagi- Uda Antennas Using Computational Intelligence. IEEE Transactions on Antennas and Propagation,, 52(7):1811– 1818, 2004.
  31. H. J. Wang, K. F. Man, C. H. Chan, and K. M. Luk. Optimization of Yagi array by Hierarchical Genetic Algorithms. IEEE, 1:91–94, 2003.
  32. H. Yagi. Beam Transmission of Ultra Short Waves. Proceedings of the Institute of Radio Engineers, 16(6):715– 740, 1928.
Index Terms

Computer Science
Information Sciences

Keywords

Yagi-Uda Antenna Bio-geography Based Optimization (BBO) Migration Variants Enhanced BBO Immigration Refusal BBO Blended BBOifx

Powered by PhDFocusTM