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首页> 外文期刊>International Journal of Computational Intelligence and Applications >A Crossover Improved Genetic Algorithm and Its Application in Non-Uniform Linear Antenna Arrays
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A Crossover Improved Genetic Algorithm and Its Application in Non-Uniform Linear Antenna Arrays

机译:交叉改进的遗传算法及其在非均匀线性天线阵列中的应用

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Genetic Algorithm (GA) is a widely used optimization technique with multitudinous applications. Improving the performance of the GA would further augment its functionality. This paper presents a Crossover Improved GA (CIGA) that emulates the motion of fireflies employed in the Fire°y Algorithm (FA). By employing this mimicked crossover operation, the overall performance of the GA is greatly enhanced. The CIGA is tested on 14 benchmark functions conjointly with the other existing optimization techniques to establish its superiority. Finally, the CIGA is applied to the practical optimization problem of synthesizing non-uniform linear antenna arrays with low side lobe levels (SLL) and low beam width, both requirements being incompatible. However, the proposed CIGA applied for the synthesis of a 12 element array yields an SLL of -29.2 dB and a reduced beam width of 19.1°.
机译:遗传算法(GA)是一种广泛应用的优化技术,具有众多应用。 提高GA的性能将进一步增强其功能。 本文介绍了一种交叉改进的GA(CIGA),其模拟了火灾°Y算法(FA)中使用的萤火虫的运动。 通过采用这种模拟的交叉操作,GA的整体性能大大提高。 CIGA在14个基准功能上进行测试,与其他现有优化技术合作,以确定其优越性。 最后,CIGA应用于合成具有低侧凸电平(SLL)和低光束宽度的非均匀线性天线阵列的实际优化问题,这两个要求都不兼容。 然而,施加用于合成12个元素阵列的所提出的CIGA产生-29.2dB的SLL,并且减少的光束宽度为19.1°。

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