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Construction methods of basal evolutionary operators of mind evolutionary computation

机译:思维进化计算的基础进化算子的构造方法

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MEC, Mind Evolutionary Computation presented in Literature has superiority for solving the premature convergence problem of genetic algorithm and no-numerical optimization. The method is a new algorithm, the mature evolutionary operators have not come into being, so the efficiency is lower. For the problem that the characteristics can be discrete, the concept of Information Matrix is introduced, the construction methods of the generic similartaxis and dissimilation operators are given in the paper, the coding method for this kind of problem is solved, the theory becomes more perfect, and the effectiveness is proven through the computing examples.
机译:文献中提出的MEC,思维进化计算在解决遗传算法的过早收敛问题和无数值优化方面具有优势。该方法是一种新算法,尚未形成成熟的进化算子,因此效率较低。针对特征可以离散的问题,介绍了信息矩阵的概念,给出了通用相似轴和异化算子的构造方法,解决了此类问题的编码方法,使理论变得更加完善。 ,并且通过计算示例证明了其有效性。

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