@inproceedings{930b378584d04a359ef1eba328a3bf56,
title = "A Weed Invasion and Genetic Hybrid Algorithm in Linear Sparse Array Synthesis",
abstract = "This paper proposed and implemented an genetic and weed invasion hybrid algorithm in Sparse Array Synthesis. The classical weed invasion algorithm has high requirements on the convergence parameters in the process of generating weeds from seeds. Inappropriate parameters can easily lead to local convergence of evolution. The mutation and crossover operations similar to the genetic algorithm were introduced into the classical weed invasion algorithm. The method improves convergence speed, avoids local convergence, and enhances the stability of the algorithm. The algorithm is used in practical application in the synthesis of linear sparsely distributed array pattern, and the predetermined index is obtained through calculation. At the same time, compared with the genetic algorithm and the classical weed invasion algorithm, the results show that the hybrid algorithm has certain advantages.",
keywords = "pattern synthesis, sparse array, weed invasion algorithm",
author = "He, {Long Wei} and Qiang Li and Xiaofei Wang and Zhou, {Shi Gang} and Wei Wang",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022 ; Conference date: 09-12-2022 Through 12-12-2022",
year = "2022",
doi = "10.1109/ACES-China56081.2022.10064832",
language = "英语",
series = "2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022",
}