Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning
The artificial bee colony (ABC) algorithm is a recently introduced optimization method in the research field of swarm intelligence. This paper presents an improved ABC algorithm named as OGABC based on opposition-based learning (OBL) and global best search equation to overcome the shortcomings of th...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2016/2749035 |
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| _version_ | 1832556094833033216 |
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| author | Chao Yang Jian-Ke Zhang Li-Xin Guo |
| author_facet | Chao Yang Jian-Ke Zhang Li-Xin Guo |
| author_sort | Chao Yang |
| collection | DOAJ |
| description | The artificial bee colony (ABC) algorithm is a recently introduced optimization method in the research field of swarm intelligence. This paper presents an improved ABC algorithm named as OGABC based on opposition-based learning (OBL) and global best search equation to overcome the shortcomings of the slow convergence rate and sinking into local optima in the process of inversion of atmospheric duct. Taking the inversion of the surface duct using refractivity from clutter (RFC) technique as an example to validate the performance of the proposed OGABC, the inversion results are compared with those of the modified invasive weed optimization (MIWO) and ABC. The radar sea clutter power calculated by parabolic equation method using the simulated and measured refractivity profile is utilized to carry out the inversion of the surface duct, respectively. The comparative investigation results indicate that the performance of OGABC is superior to that of MIWO and ABC in terms of stability, accuracy, and convergence rate during the process of inversion. |
| format | Article |
| id | doaj-art-d5ad94bf2806419fb3d4dd015fcfaefa |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-d5ad94bf2806419fb3d4dd015fcfaefa2025-02-03T05:46:23ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772016-01-01201610.1155/2016/27490352749035Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based LearningChao Yang0Jian-Ke Zhang1Li-Xin Guo2School of Science, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaSchool of Science, Xi’an University of Posts and Telecommunications, Xi’an 710121, ChinaSchool of Physics and Optoelectronic Engineering, Xidian University, Xi’an 710071, ChinaThe artificial bee colony (ABC) algorithm is a recently introduced optimization method in the research field of swarm intelligence. This paper presents an improved ABC algorithm named as OGABC based on opposition-based learning (OBL) and global best search equation to overcome the shortcomings of the slow convergence rate and sinking into local optima in the process of inversion of atmospheric duct. Taking the inversion of the surface duct using refractivity from clutter (RFC) technique as an example to validate the performance of the proposed OGABC, the inversion results are compared with those of the modified invasive weed optimization (MIWO) and ABC. The radar sea clutter power calculated by parabolic equation method using the simulated and measured refractivity profile is utilized to carry out the inversion of the surface duct, respectively. The comparative investigation results indicate that the performance of OGABC is superior to that of MIWO and ABC in terms of stability, accuracy, and convergence rate during the process of inversion.http://dx.doi.org/10.1155/2016/2749035 |
| spellingShingle | Chao Yang Jian-Ke Zhang Li-Xin Guo Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning International Journal of Antennas and Propagation |
| title | Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning |
| title_full | Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning |
| title_fullStr | Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning |
| title_full_unstemmed | Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning |
| title_short | Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning |
| title_sort | investigation on the inversion of the atmospheric duct using the artificial bee colony algorithm based on opposition based learning |
| url | http://dx.doi.org/10.1155/2016/2749035 |
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