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改进遗传算法Matlab代码

于 2020-06-17 发布
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说明:  图像阈值分割技术在图像分割中具有重要的意义。遗传算法既可以对全局信 息高效利用,也减少了存储空间和计算量。利用遗传算法的优点,提出了一 种用改进遗传算法的图像分割的方法,可以将父代中适应度大的个体代替当前代 中的个体,保证了可以选出最优的个体。遗传算法是具有鲁棒性和自适应性的搜 索方法.通过实验对比,表明该方法具有快速、稳定分割的特点。(Image threshold segmentation technology is of great significance in image segmentation. Genetic Algorithms can be used for global information Efficient utilization of information also reduces storage space and computation. Based on the advantages of genetic algorithm, a new genetic algorithm is proposed. A method of image segmentation based on improved genetic algorithm can replace the current generation with individuals with large adaptability in the parent generation. The individual in the system ensures that the best individual can be selected. Genetic Algorithms are Robust and Adaptive Search The experimental comparison shows that the method has the characteristics of fast and stable segmentation.)

文件列表:

改进遗传算法Matlab代码, 0 , 2019-08-10
改进遗传算法Matlab代码\crossover.m, 582 , 2018-08-30
改进遗传算法Matlab代码\findresult.m, 389 , 2018-08-31
改进遗传算法Matlab代码\fitness_order.m, 3605 , 2018-08-28
改进遗传算法Matlab代码\generation.m, 195 , 2018-08-28
改进遗传算法Matlab代码\initpop.m, 286 , 2018-08-28
改进遗传算法Matlab代码\main.asv, 815 , 2018-08-30
改进遗传算法Matlab代码\main.m, 915 , 2018-08-31
改进遗传算法Matlab代码\mutation.m, 584 , 2018-08-31
改进遗传算法Matlab代码\select.m, 1415 , 2018-08-28

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