李静

• 1:重庆工程学院
• 2:重庆市数字影视与新媒体工程技术研究中心

摘要(Abstract)：

针对传统遗传算法在数据特征分类过程中容易陷入局部最佳解,分类结果识别率以及准确率较低的问题,提出基于改进遗传算法的数据特征分类方法。采用模拟退火法对遗传算法实施改进,遗传算法经过设置参数、适应度函数的设计、选择策略、交叉策略以及终止条件等过程得到粗糙数据特征分类结果。采用模拟退火算法通过概率突跳特性在温度下降时随机获取目标函数的全局最优解,基于Meteopolis准则提高算法局部寻优效率,通过模拟退火算法对遗传算法的交叉概率与变异概率的选择过程实施改进,获取高精度的数据特征分类结果。实验结果表明,所提方法数据特征分类识别率以及准确率高,分类耗时低。

关键词(KeyWords)： 改进遗传算法;数据特征分类;模拟退火;局部寻优;Meteopolis准则;概率突跳特性

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目(61272043)~~

作者(Author): 李静

DOI: 10.16652/j.issn.1004-373x.2018.14.041

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