2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting 2019
DOI: 10.1109/apusncursinrsm.2019.8889004
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Surface Reconstruction of Large Reflector Antennas Based on a Hybrid of CMA-ES and HIO Algorithms

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Cited by 3 publications
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“…CMA-ES handles the pairwise dependencies between sample points by the covariance matrix and generates new samples with a multivariate normal distribution [24]. Therefore, the CMA-ES algorithm is often used to improve the global search performance of other algorithms [21,25]. Selecting it as the other algorithm for hybridization, we propose a new Segmented Hybrid PSO and CMA-ES (SHPC) algorithm.…”
Section: Segmented Hybrid Pso and Cma-es Algorithmmentioning
confidence: 99%
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“…CMA-ES handles the pairwise dependencies between sample points by the covariance matrix and generates new samples with a multivariate normal distribution [24]. Therefore, the CMA-ES algorithm is often used to improve the global search performance of other algorithms [21,25]. Selecting it as the other algorithm for hybridization, we propose a new Segmented Hybrid PSO and CMA-ES (SHPC) algorithm.…”
Section: Segmented Hybrid Pso and Cma-es Algorithmmentioning
confidence: 99%
“…i ; Update G best : If f (x i ) is better than the fitness value of G best , then G best is set to the position of the current particle x i ; Update velocities: Calculate velocities v i using Equation(25).If v i > v max then v i = v max .If v i < v min then v i = v min ;Update positions: Calculate positions x i using Equation (26); (H < 100 & K > 100) (Execute CMA-ES algorithm) Initialize population of CMA-ES (set G best as the m at CMA-ES) FOR (each individual i) Update x i : Generating new individuals using the Gaussian distribution by Equation (27). Calculate fitness: Calculate the fitness value of the current individuals: f (x i ).…”
mentioning
confidence: 99%