Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization

An Nan; Bao Liyong

doi:doi:10.11648/j.ijics.20220704.11

| Peer-Reviewed

Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization

An Nan, Bao Liyong

Published in International Journal of Information and Communication Sciences (Volume 7, Issue 4)

Received: 19 September 2022 Accepted: 24 October 2022 Published: 28 October 2022

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Aiming at the problems of computing complexity, long time-consuming and low accuracy in the process of antenna optimization design, a particle swarm optimization algorithm based on chaotic ergodic search is proposed in this paper. In order to improve the rationality of the selection of the initial population of the traditional particle swarm optimization algorithm and enhance the diversity of particles in the iterative process of the algorithm, this algorithm introduces a uniform Logistic chaotic map into the traditional particle swarm optimization algorithm, so as to improve the convergence speed and optimization performance of the particle swarm optimization more effectively. In this paper, the Logistic map is selected in the chaotic map, and the analysis shows that although it has good long-term periodicity and initial value sensitivity, the data does not obey the uniform distribution, which makes the omission range when the sequence value is small, which reduces the chaos. The efficiency of traversal, in view of this shortcoming, this paper proposes a method of homogenizing Logistic, and deduces and analyzes it. It is concluded that this homogenized Logistic method has better randomness and can better reflect the characteristics of uniform distribution of data. Further, based on the optimization algorithm, the rectangular microstrip antennas with two feeding modes are optimized, and the antenna size obtained by empirical formula is modeled and analyzed in HFSS software. The research results show that the optimization algorithm in this paper can bring faster convergence speed and more accurate optimization results for antenna optimization.

Published in	International Journal of Information and Communication Sciences (Volume 7, Issue 4)
DOI	10.11648/j.ijics.20220704.11
Page(s)	82-91
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Antenna Optimization, Homogenized Chaotic Mapping, Particle Swarm Optimization, Microstrip Antenna

References

[1]	ZHANG Min, QU Peihua, YANG Song. Application of evolutionary algorithm in optimization of microstrip antenna [J]. Chinese Journal of Radio Science, 2014, 29 (3): 571-575.
[2]	R. Munson. Conformal microstrip antennas and microstrip phased arrays [J]. IEEE Transactions on Antennas and Propagation, 1974, 22 (1): 74-78.
[3]	W. F. Richards, Y. T. Lo, D. D. Harrison. Improved theory for microstrip antennas [J]. Electronics Letters, 1979, 15 (2): 42-44.
[4]	E. Newman, P. Tulyathan. Analysis of microstrip antennas using moment methods [J] IEEE Transactions on Antennas and Propagation [J]. 1981, 29 (1): 47-53.
[5]	TANG Linying, WANG Lianhong, LI Xiaoyao. The artificial physics optimization algorithm based on conjugate gradient method and tent mapping [J]. Computer Applications and Software, 2017, 34 (2): 246-250.
[6]	Yanjing H, Shibiao HE, Cheng GU, et al. Method of chaotic signals estimation and track based on improved logistic map [J]. Computer applied research, 2012, 29 (11): 4152-4155.
[7]	ZHANG Ziye. Research on Radiation and scattering Characteristics of Microstrip Antenna [D]. Beijing Jiaotong University, 2018.
[8]	HU Yilue. Optimization and Design of Microstrip Antenna Based on Genetic Algorithm [D]. Shanghai Normal University, 2019.
[9]	ZHANG Qing. Based on Improved Chaos Mapping Particle Swarm Optimization Algorithm and Its Application on Optimization of Antenna Parameters [D]. Yunnan University, 2018.
[10]	Manotosh Biswas, Mausumi Sen. Fast and accurate model for a coax-fed rectangular patch antenna with varying aspect ratio, feed location and substrate electrical parameters [J]. Journal of Electromagnetic Waves and Applications, 2019, 33 (4).
[11]	Rui Xue, Ju Feng, Dapeng Liu, Cheng Liao. Optimization of OAM array antenna based on PSO algoriyhm [C]. Papers Collection of the National Antenna Annual Conference 2021, 2021: 847-849.
[12]	NI Long-Yu, FU Qiang, WU Cang-Chen. Monarchs Butterfly Optimization Algorithm Based on Logistic Chaotic Map Optimization [J]. Computer Systems & Applications, 2021, 30 (7): 150−157.
[13]	WU Dingjie, ZHOU Qingxing，WEN Lishu. Improved sparrow algorithm based on Logistic chaos mapping [J]. Journal of Science of Teachers′ College and University, 2021, 41 (06): 10-15.
[14]	Lu Hao, Xu Xiaofei. Comparative study of miniaturized microstrip antennas designed with different super-substrate materials operating at 900 MHz [J]. Applied Physics A, 2022, 128 (4).
[15]	Lin Jiayu, Zhao Kangnan, Cai Xin, Li Danning, Wang Zuxi. An Image Encryption Method Based on Logistic Chaotic Mapping and DNA Coding [J]. MIPPR 2019: REMOTE SENSING IMAGE PROCESSING, GEOGRAPHIC INFORMATION SYSTEMS, AND OTHER APPLICATIONS, 2020, 11432.
[16]	Zhan Bangshun, An Shun, He Yan, Wang Longjin. Three-Dimensional Path Planning for AUVs Based on Standard Particle Swarm Optimization Algorithm [J]. Journal of Marine Science and Engineering, 2022, 10 (9).
[17]	Li Di, Wang Xianglong, Chen Dongdong, Zhang Qidong, Yang Yintang. A precise ultra-wideband ranging method using pre-corrected strategy and particle swarm optimization algorithm [J]. Measurement, 2022, 194.
[18]	Eslami Nazari Mohsen, Huang Weimin, Alavizadeh Zahraalsadat. Return loss-bandwidth evaluation for electrically small microstrip antennas [J]. Journal of Electromagnetic Waves and Applications, 2020, 34 (16).

Cite This Article

Plain Text BibTeX RIS

APA Style

An Nan, Bao Liyong. (2022). Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization. International Journal of Information and Communication Sciences, 7(4), 82-91. https://doi.org/10.11648/j.ijics.20220704.11

Copy | Download

ACS Style

An Nan; Bao Liyong. Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization. Int. J. Inf. Commun. Sci. 2022, 7(4), 82-91. doi: 10.11648/j.ijics.20220704.11

Copy | Download

AMA Style

An Nan, Bao Liyong. Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization. Int J Inf Commun Sci. 2022;7(4):82-91. doi: 10.11648/j.ijics.20220704.11

Copy | Download

@article{10.11648/j.ijics.20220704.11,
  author = {An Nan and Bao Liyong},
  title = {Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization},
  journal = {International Journal of Information and Communication Sciences},
  volume = {7},
  number = {4},
  pages = {82-91},
  doi = {10.11648/j.ijics.20220704.11},
  url = {https://doi.org/10.11648/j.ijics.20220704.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijics.20220704.11},
  abstract = {Aiming at the problems of computing complexity, long time-consuming and low accuracy in the process of antenna optimization design, a particle swarm optimization algorithm based on chaotic ergodic search is proposed in this paper. In order to improve the rationality of the selection of the initial population of the traditional particle swarm optimization algorithm and enhance the diversity of particles in the iterative process of the algorithm, this algorithm introduces a uniform Logistic chaotic map into the traditional particle swarm optimization algorithm, so as to improve the convergence speed and optimization performance of the particle swarm optimization more effectively. In this paper, the Logistic map is selected in the chaotic map, and the analysis shows that although it has good long-term periodicity and initial value sensitivity, the data does not obey the uniform distribution, which makes the omission range when the sequence value is small, which reduces the chaos. The efficiency of traversal, in view of this shortcoming, this paper proposes a method of homogenizing Logistic, and deduces and analyzes it. It is concluded that this homogenized Logistic method has better randomness and can better reflect the characteristics of uniform distribution of data. Further, based on the optimization algorithm, the rectangular microstrip antennas with two feeding modes are optimized, and the antenna size obtained by empirical formula is modeled and analyzed in HFSS software. The research results show that the optimization algorithm in this paper can bring faster convergence speed and more accurate optimization results for antenna optimization.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization
AU  - An Nan
AU  - Bao Liyong
Y1  - 2022/10/28
PY  - 2022
N1  - https://doi.org/10.11648/j.ijics.20220704.11
DO  - 10.11648/j.ijics.20220704.11
T2  - International Journal of Information and Communication Sciences
JF  - International Journal of Information and Communication Sciences
JO  - International Journal of Information and Communication Sciences
SP  - 82
EP  - 91
PB  - Science Publishing Group
SN  - 2575-1719
UR  - https://doi.org/10.11648/j.ijics.20220704.11
AB  - Aiming at the problems of computing complexity, long time-consuming and low accuracy in the process of antenna optimization design, a particle swarm optimization algorithm based on chaotic ergodic search is proposed in this paper. In order to improve the rationality of the selection of the initial population of the traditional particle swarm optimization algorithm and enhance the diversity of particles in the iterative process of the algorithm, this algorithm introduces a uniform Logistic chaotic map into the traditional particle swarm optimization algorithm, so as to improve the convergence speed and optimization performance of the particle swarm optimization more effectively. In this paper, the Logistic map is selected in the chaotic map, and the analysis shows that although it has good long-term periodicity and initial value sensitivity, the data does not obey the uniform distribution, which makes the omission range when the sequence value is small, which reduces the chaos. The efficiency of traversal, in view of this shortcoming, this paper proposes a method of homogenizing Logistic, and deduces and analyzes it. It is concluded that this homogenized Logistic method has better randomness and can better reflect the characteristics of uniform distribution of data. Further, based on the optimization algorithm, the rectangular microstrip antennas with two feeding modes are optimized, and the antenna size obtained by empirical formula is modeled and analyzed in HFSS software. The research results show that the optimization algorithm in this paper can bring faster convergence speed and more accurate optimization results for antenna optimization.
VL  - 7
IS  - 4
ER  -

Copy | Download

Author Information

An Nan

School of Information, Yunnan University, Kunming, China
Bao Liyong

School of Information, Yunnan University, Kunming, China

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

An Nan, Bao Liyong. (2022). Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization. International Journal of Information and Communication Sciences, 7(4), 82-91. https://doi.org/10.11648/j.ijics.20220704.11

Copy | Download

ACS Style

An Nan; Bao Liyong. Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization. Int. J. Inf. Commun. Sci. 2022, 7(4), 82-91. doi: 10.11648/j.ijics.20220704.11

Copy | Download

AMA Style

An Nan, Bao Liyong. Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization. Int J Inf Commun Sci. 2022;7(4):82-91. doi: 10.11648/j.ijics.20220704.11

Copy | Download

@article{10.11648/j.ijics.20220704.11,
  author = {An Nan and Bao Liyong},
  title = {Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization},
  journal = {International Journal of Information and Communication Sciences},
  volume = {7},
  number = {4},
  pages = {82-91},
  doi = {10.11648/j.ijics.20220704.11},
  url = {https://doi.org/10.11648/j.ijics.20220704.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijics.20220704.11},
  abstract = {Aiming at the problems of computing complexity, long time-consuming and low accuracy in the process of antenna optimization design, a particle swarm optimization algorithm based on chaotic ergodic search is proposed in this paper. In order to improve the rationality of the selection of the initial population of the traditional particle swarm optimization algorithm and enhance the diversity of particles in the iterative process of the algorithm, this algorithm introduces a uniform Logistic chaotic map into the traditional particle swarm optimization algorithm, so as to improve the convergence speed and optimization performance of the particle swarm optimization more effectively. In this paper, the Logistic map is selected in the chaotic map, and the analysis shows that although it has good long-term periodicity and initial value sensitivity, the data does not obey the uniform distribution, which makes the omission range when the sequence value is small, which reduces the chaos. The efficiency of traversal, in view of this shortcoming, this paper proposes a method of homogenizing Logistic, and deduces and analyzes it. It is concluded that this homogenized Logistic method has better randomness and can better reflect the characteristics of uniform distribution of data. Further, based on the optimization algorithm, the rectangular microstrip antennas with two feeding modes are optimized, and the antenna size obtained by empirical formula is modeled and analyzed in HFSS software. The research results show that the optimization algorithm in this paper can bring faster convergence speed and more accurate optimization results for antenna optimization.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Particle Swarm Algorithm Based on Homogenized Logistic Mapping and Its Application in Antenna Parameter Optimization
AU  - An Nan
AU  - Bao Liyong
Y1  - 2022/10/28
PY  - 2022
N1  - https://doi.org/10.11648/j.ijics.20220704.11
DO  - 10.11648/j.ijics.20220704.11
T2  - International Journal of Information and Communication Sciences
JF  - International Journal of Information and Communication Sciences
JO  - International Journal of Information and Communication Sciences
SP  - 82
EP  - 91
PB  - Science Publishing Group
SN  - 2575-1719
UR  - https://doi.org/10.11648/j.ijics.20220704.11
AB  - Aiming at the problems of computing complexity, long time-consuming and low accuracy in the process of antenna optimization design, a particle swarm optimization algorithm based on chaotic ergodic search is proposed in this paper. In order to improve the rationality of the selection of the initial population of the traditional particle swarm optimization algorithm and enhance the diversity of particles in the iterative process of the algorithm, this algorithm introduces a uniform Logistic chaotic map into the traditional particle swarm optimization algorithm, so as to improve the convergence speed and optimization performance of the particle swarm optimization more effectively. In this paper, the Logistic map is selected in the chaotic map, and the analysis shows that although it has good long-term periodicity and initial value sensitivity, the data does not obey the uniform distribution, which makes the omission range when the sequence value is small, which reduces the chaos. The efficiency of traversal, in view of this shortcoming, this paper proposes a method of homogenizing Logistic, and deduces and analyzes it. It is concluded that this homogenized Logistic method has better randomness and can better reflect the characteristics of uniform distribution of data. Further, based on the optimization algorithm, the rectangular microstrip antennas with two feeding modes are optimized, and the antenna size obtained by empirical formula is modeled and analyzed in HFSS software. The research results show that the optimization algorithm in this paper can bring faster convergence speed and more accurate optimization results for antenna optimization.
VL  - 7
IS  - 4
ER  -

Copy | Download