Study on pattern synthesis of conformal array using enhanced adaptive genetic algorithm

Seong, Cheol-Min; Park, Dong-Chul

doi:10.1002/mop.29037

Cited by 10 publications

(4 citation statements)

References 13 publications

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“…AGA는 GA에 비해 수렴 속도와 최적화 값 을 개선시켰지만, 여전히 우성 유전자를 가진 부모군을 통해 자손을 생성하므로 지역해에 빠져 선수렴될 가능성 이 높다. 본 연구팀에서는 이를 개선하기 위해 IWO(Invasive Weed Optimization) [20] 의 종자 및 전체 후보군의 생산 절 차를 AGA에 적용시킨 EAGA(Enhanced Adaptive Genetic Algorithm)을 제안하였으며 [14], [15] , 검증함수와 패턴 합성 을 통해 제안된 알고리즘의 우수성을 확인한 바 있다. 전 체적인 EAGA의 동작을 그림 6에 나타내었다.…”

Section: 컨포멀 배열 안테나의 패턴 합성 이론과unclassified

“…합성 대상 안테나는 두 가 지로, 각각 항공기의 날개와 동체에 적용할 수 있는 2차 함수 형태의 단일 곡면형 컨포멀 배열 안테나와 항공기 의 앞부분에 적용할 수 있는 2차 함수의 회전체형 컨포멀 배열 안테나이다. 최적화된 패턴을 합성하기 위해 EAGA (Enhanced Adaptive Genetic Algorithm)을 이용하였다 [14] . 표현되는 2차 함수 곡선형 도체 위에 배열된 안테나의 원 거리장 패턴을 고찰해 보자 [15] .…”

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Study on Pattern Synthesis of Conformal Phased Array Antenna

Park¹,

Kwon²,

Ryu³

et al. 2015

The Journal of Korean Institute of Electromagnetic Engineering

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This paper describes the pattern synthesis method of two kinds of conformal array antenna using the Enhanced Adaptive Genetic Algorithm (EAGA). One is the 1×16 conformal array antenna on a curved cylindrical metallic surface with quadratic function, and the other is the 18-element conformal arrary antenna on a metallic surface obtained by the rotation of a quadratic function curve around the axis. The active element pattern is utilized in the pattern synthesis. Especially for the case of the rotated-type conformal array antenna the transformed active element pattern obtained from the Euler's angle rotation of the active element pattern of the planar concentric array is utilized, which reduces the synthesis time a lot. To verify the validity of the proposed synthesis method the MATLAB results are compared with the MWS results. Furthermore, for the case of 1×16 conformal array antenna the measured results are compared with the MATLAB synthesized results.

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Section: 컨포멀 배열 안테나의 패턴 합성 이론과unclassified

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Study on Pattern Synthesis of Conformal Phased Array Antenna

Park¹,

Kwon²,

Ryu³

et al. 2015

The Journal of Korean Institute of Electromagnetic Engineering

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“…Results demonstrate that this algorithm is better at finding global optimal solutions. Seong et al [ 22 ] proposed an enhanced adaptive genetic algorithm which combines an adaptive genetic algorithm (AGA) with conventional invasive weeds optimization (IWO) technology. This combination improved search capability and convergence speed.…”

Section: Introductionmentioning

confidence: 99%

Predicting human body composition using a modified adaptive genetic algorithm with a novel selection operator

et al. 2020

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Background Changes to human body composition reflect changes in health status to some extent. It has been recognized that these changes occur earlier than diseases. This means that a reasonable prediction of body composition helps to improve model users’ health. To overcome the low accuracy and poor adaptability of existing human body composition prediction models and obtain higher efficiency, we proposed a novel method for predicting human body composition which uses a modified adaptive genetic algorithm (MAGA). Methods Firstly, since there are many parameters for a human body composition model, and these parameters are associated, we designed a new parameter selection approach by combining the improved RReliefF method with the mRMR method. Following this, selected parameters were used to establish a model that fits body composition. Secondly, in order to accurately calculate the weight of parameters in this model, we proposed a solution which used a modified adaptive genetic algorithm, taking advantage of both roulette and optimum reservation strategies. This solution also has an improved selection operator. Thirdly, taking the percentage of body fat (PBF) as an example of body composition, we conducted experiments to compare performance between our algorithm and other algorithms. Results Through our simulations, we demonstrated that the adaptability of the proposed model is 0.9921, the mean relative error is 0.05%, the mean square error is 1.3 and the correlation coefficient is 0.982. When compared with the indexes of other models, our model has the highest adaptability and the smallest error. Additionally, the suggested model, which has a training time of 28.58s and a running time of 2.84s, is faster than some models. Conclusion The PBF prediction model established by MAGA has high accuracy, stronger generalization ability and higher efficiency, which could provide a new method for human composition prediction.

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“…12 In the literature, various techniques and algorithms have been developed to achieve the desired radiation pattern characteristics in antenna arrays. Several probabilistic or evolutionary optimization techniques such as Particle Swarm Optimization (PSO), 13 Genetic Algorithm (GA), 14 Taguchi algorithm, 15 and Differential Evolution (DE) algorithm 16 have been used to control and correct the radiation pattern. These optimization methods iteratively search, evaluate and improve the parameters to determine the best-fitted results.…”

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Radiation pattern synthesis in conformal antenna arrays using modified convex optimization technique

Khan

Khattak

Asif

et al. 2022

Int J RF Mic Comp-Aid Eng

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In this paper, a modified convex optimization technique is used for radiation pattern correction in a cylindrical-shaped conformal microstrip array antenna.The technique uses numerical simulations to optimize the amplitude and phase excitations, with the goal to decrease the Euclidean distance between the desired field pattern and the obtained (simulated/measured) field pattern while maintaining the main beam direction, null's location, and side lobe levels under control. Two prototypes of 1 Â 4 and 2 Â 4 conformal microstrip antenna array deformed from linear/planar structure to the prescribed cylindrical shape, with different radii of curvature, are studied to demonstrate the performance of the proposed technique. The proposed convex optimization model when applied to conformal antenna array possesses fast computing speed and high convergence accuracy for radiation pattern synthesis, which can be a valuable tool for engineering applications.

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Study on pattern synthesis of conformal array using enhanced adaptive genetic algorithm

Cited by 10 publications

References 13 publications

Study on Pattern Synthesis of Conformal Phased Array Antenna

Study on Pattern Synthesis of Conformal Phased Array Antenna

Predicting human body composition using a modified adaptive genetic algorithm with a novel selection operator

Radiation pattern synthesis in conformal antenna arrays using modified convex optimization technique

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