通信学报2017，Vol.38Issue(2)：1-9,9.DOI:10.11959/j.issn.1000-436x.2017022
混合编码方式的图像聚类算法
Image cluster algorithm of hybrid encoding method
摘要
Abstract
In the clustering analysis based on swarm intelligence optimization algorithm, the most of encoding method only used single form, and this method might be limit range of search space, the algorithm was easy to fall into local op-timum. In order to solve this problem, image clustering algorithm of hybrid encoding (HEICA) was proposed. Firstly, a hybrid encoding model based on image clustering was established, this method could expand the scope of the search space. Meanwhile, it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO), this method could improve the global search capability. In the simulation experiment, it was carried out to illustrate the performance of the proposed method based on four datasets. Compared with results form four measured cluster algorithm. The experimental results show that the algorithm has strong global search capability, high stability and clustering effect.关键词
图像聚类分析/混合编码/雨林算法/量子粒子群Key words
image cluster analysis/hybrid encoding/rain forest algorithm/quantum particle swarm optimization分类
信息技术与安全科学引用本文复制引用
赵春晖,李雪源,崔颖..混合编码方式的图像聚类算法[J].通信学报,2017,38(2):1-9,9.基金项目
国家自然科学基金资助项目(No.61405041, No.61571145) （No.61405041, No.61571145）
黑龙江省自然科学基金资助项目(No.ZD201216) （No.ZD201216）
黑龙江省博士后特别基金资助项目(No.LBH-TZ0420)The National Natural Science Foundation of China(No.61405041, No.61571145), The Natural Science Founda-tion of Heilongjiang Province (No.ZD201216), Heilongjiang Postdoctoral Special Scholars Foundation(No.LBH-TZ0420) （No.LBH-TZ0420）
