Application of a parallel particle swarm optimization scheme to the design of electromagnetic absorbers

Cui, Shuai; Weile, D.S.

doi:10.1109/tap.2005.858866

Cited by 92 publications

(39 citation statements)

References 15 publications

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“…The application of PSO optimizers in electromagnetic design problems has attracted several researchers [8][9][10][11][12][13][14][15][16][17]. PSO has also been used successfully in absorber design problems [18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Design of microwave broadband absorbers using a self-adaptive differential evolution algorithm

Goudos

2008

Int J RF and Microwave Comp Aid Eng

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Section: Introductionmentioning

confidence: 99%

Design of microwave broadband absorbers using a self-adaptive differential evolution algorithm

Goudos

2008

Int J RF and Microwave Comp Aid Eng

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“…Both discrete and continuous parameters and parallel computing implementation are achieved using the PSO. 39,40 Because of these advantages, PSO is used as the optimization search method in our study.…”

Section: Psomentioning

confidence: 99%

A non-line-of-sight error mitigation method for location estimation

Chen

2017

International Journal of Distributed Sensor Networks

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Because there are always non-line-of-sight effects in signal propagation, researchers have proposed various algorithms to mitigate the measured error caused by non-line-of-sight. Initially inspired by flocking birds, particle swarm optimization is an evolutionary computation tool for optimizing a problem by iteratively attempting to improve a candidate solution with respect to a given measure of quality. In this article, we propose a new location algorithm that uses time-of-arrival measurements to improve the mobile station location accuracy when three base stations are available. The proposed algorithm uses the intersections of three time-of-arrival circles based on the particle swarm optimization technique to give a location estimation of the mobile station in non-line-of-sight environments. An object function is used to establish the nonlinear relationship between the intersections of the three circles and the mobile station location. The particle swarm optimization finds the optimal solution of the object function and efficiently determines the mobile station location. The simulation results show that the proposed algorithm performs better than the related algorithms in wireless positioning systems, even in severe non-line-of-sight propagation conditions.

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“…In the case of a specific frequency range, how to choose materials and their thickness to minimize the reflection coefficient of the absorber can be considered as an optimization problem. In recent years, heuristic algorithms such as genetic algorithm (GA) [1][2][3], particle swarm optimization (PSO) [4][5][6], differential evolution (DE) [7,8], and central force optimization (CFO) [9] have solved this problem. Although these algorithms optimize multilayer absorbers that minimize the reflection coefficient of the incident wave at multiple angles of incidence and in different frequency ranges, the thickness and reflection coefficient of the absorbers that they obtain can be further reduced.…”

Section: Introductionmentioning

confidence: 99%

Design of Multilayer Microwave Absorbers Using Hybrid Binary Lightning Search Algorithm and Simulated Annealing

Lu¹,

Zhou²

2017

PIER B

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Abstract-In this paper, a hybrid algorithm of binary lightning search algorithm and simulated annealing (BLSA-SA) is proposed to optimize the design of multilayer microwave absorbers for normal incidence. The multilayer absorber is designed to find a set of coatings that minimize the reflection coefficient over the desired frequency. The design problem is translated into solving the binary problem. Three different design examples are presented to verify the performance of the BLSA-SA. The results show that the reflection coefficient and thickness of BLSA-SA are better than those of other heuristic algorithms for multilayer absorber design. In the five-layer design, the standard deviation of BLSA-SA is the smallest among the 20 independent test results of the algorithms, which indicates that the BLSA-SA algorithm, has a strong stability.

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Application of a parallel particle swarm optimization scheme to the design of electromagnetic absorbers

Cited by 92 publications

References 15 publications

Design of microwave broadband absorbers using a self-adaptive differential evolution algorithm

Design of microwave broadband absorbers using a self-adaptive differential evolution algorithm

A non-line-of-sight error mitigation method for location estimation

Design of Multilayer Microwave Absorbers Using Hybrid Binary Lightning Search Algorithm and Simulated Annealing

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