基于PSO粒子群优化的聚类数字识别仿真,+word论文。

上传者: ccsss22 | 上传时间: 2022-04-30 09:09:23 | 文件大小: 617KB | 文件类型: RAR
粒子群优化与其它基于群体的进化算法相比,它们均初始化为一组随机解,通过迭代搜寻最优解。PSO将每一个可能产生的解表述为群中的一个微粒,每个微粒都具有自己的位置向量和速度向量,以及一个由目标函数决定的适应度。本文首先介绍了基本的粒子群算法的理论和基本算法流程,然后介绍了模糊聚类的相关知识。从而对基于粒子群的聚类分析有更进一步的认识,然后在本文的第三章,通过MATLAB对该算法进行了仿真,并通过分析几张手动输入图片进行仿真分析,发现采用不同的距离方法均能实现图片的模糊聚类。

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