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首页 » AI-NN-PR » 针对现有遗传算法在多维非线性优选方面的不足,本文提出了一种基于小生境进化算法(NEA)的非线性优选模型,探讨了NEA算法的参数选择原则。通过大量仿真和比较,表明...

针对现有遗传算法在多维非线性优选方面的不足,本文提出了一种基于小生境进化算法(NEA)的非线性优选模型,探讨了NEA算法的参数选择原则。通过大量仿真和比较,表明...

于 2023-04-07 发布 文件大小:37.14 kB
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针对现有遗传算法在多维非线性优选方面的不足,本文提出了一种基于小生境进化算法(NEA)的非线性优选模型,探讨了NEA算法的参数选择原则。通过大量仿真和比较,表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点,并能在全局范围内有效搜索所有最优解。 -against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.

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