An novel quantum genetic algorithm with Piecewise Logistic chaotic map

机译：分段逻辑混沌映射的新型量子遗传算法

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摘要

Aiming at the trouble of easy getting into local minimum and premature constringency existed in quantum genetic algorithm, this paper presents a new algorithm through analyzing the characteristic of Piecewise Logistic map. It improves the quantum genetic algorithm by using chaos optimization method based on Piecewise Logistic map and by optimizing the quantum update process through changing the rotation variation angle with the mode of fuzzy adaptive. The simulation results show that this kind of method is more effective to improve the global and local searching and to overcome the slow convergence and prematurity.

机译：针对量子遗传算法容易陷入局部极小和过早收敛的问题，通过分析分段逻辑图的特点，提出了一种新的算法。通过使用基于分段逻辑图的混沌优化方法，以及通过以模糊自适应模式改变旋转变化角来优化量子更新过程，对量子遗传算法进行了改进。仿真结果表明，这种方法对于改善全局和局部搜索以及克服收敛速度慢和早熟问题更为有效。

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《2011 Seventh International Conference on Natural Computation》|2011年|p.1053-1057|共5页
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Teng Hao; Cao Aizeng;
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正文语种
中图分类理论、方法;
关键词
Piecewise Logistic map; chaos optimization; fuzzy adaptive; quantum genetic algorithm;

机译：分段Logistic映射混沌优化模糊自适应量子遗传算法;

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An novel quantum genetic algorithm with Piecewise Logistic chaotic map

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