浏览全部资源
扫码关注微信
哈尔滨工程大学信息与通信工程学院,黑龙江 哈尔滨 150001
[ "赵春晖(1965-),男,黑龙江汤原人,博士,哈尔滨工程大学教授、博士生导师,主要研究方向为数字信号与图像处理、数字形态学与高光谱遥感图像处理等。" ]
[ "李雪源(1989-),女,辽宁盘锦人,哈尔滨工程大学博士生,主要研究方向为高光谱图像处理。" ]
[ "崔颖(1979-),女,黑龙江哈尔滨人,博士,哈尔滨工程大学副教授,主要研究方向为遥感图像处理、智能信号处理、无线传感器网络优化等。" ]
网络出版日期:2017-02,
纸质出版日期:2017-02-25
移动端阅览
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.
Chun-hui ZHAO, Xue-yuan LI, Ying CUI. Image cluster algorithm of hybrid encoding method[J]. Journal on communications, 2017, 38(2): 1-9.
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. DOI: 10.11959/j.issn.1000-436x.2017022.
Chun-hui ZHAO, Xue-yuan LI, Ying CUI. Image cluster algorithm of hybrid encoding method[J]. Journal on communications, 2017, 38(2): 1-9. DOI: 10.11959/j.issn.1000-436x.2017022.
基于群体智能优化算法的图像聚类分析,大多数都采用单一的编码方式,使搜索空间过于局限,算法很容易陷入局部最优,为了解决这个问题,提出一种混合编码方式的图像聚类分析算法(HEICA)。该算法构建一种基于图像聚类的混合编码模型,在扩大搜索空间范围的同时,与改进的雨林算法(IRFA)和量子粒子群算法(QPSO)相结合,提高全局搜索能力。在仿真实验中,采用4组数据集对算法进行聚类有效性测试,并将其与4种常用的聚类算法进行对比,实验结果表明该算法具有较强的全局搜索能力,稳定性高、聚类效果好。
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.
AHMED N . Recent review on image clustering [J ] . IET Image Proc-essing , 2015 , 9 ( 11 ): 1020 - 1032 .
陈兴蜀 , 吴小松 , 王文贤 , 等 . 基于特征关联度的K-means 初始聚类中心优化算法 [J ] . 四川大学学报(工程科学版) , 2015 , 47 ( 1 ): 13 - 19 .
CHEN X S , WU X S , WANG W X , et al . An improved initial cluster centers selection algorithm for K-means based on features correlative degree [J ] . Journal of Sichuan University (Engineering Science Edition) , 2015 , 47 ( 1 ): 13 - 19 .
李阳阳 , 石洪竺 , 焦李成 , 等 . 基于流形距离的量子进化聚类算法 [J ] . 电子学报 , 2011 , 39 ( 10 ): 2343 - 2347 .
LI Y Y , SHI H Z , JIAO L C , et al . Quantum-inspired evolutionary clustering algorithm based on manifold distance [J ] . Acta Electronica Sinica , 2011 , 39 ( 10 ): 2343 - 2347 .
AHMED N . Image clustering using exponential discriminant analysis [J ] . IET Computer Vision , 2015 , 9 ( 1 ): 1 - 12 .
罗可 , 李莲 , 周博翔 . 一种蜜蜂交配优化聚类算法 [J ] . 电子学报 , 2014 , 42 ( 12 ): 2435 - 2441 .
LUO K , LI L , ZHOU B X . A honey-bee mating optimization clustering algorithm [J ] . Acta Electronica Sinica , 2014 , 42 ( 12 ): 2435 - 2441 .
余晓东 , 雷英杰 , 岳韶华 , 等 . 基于粒子群优化的直觉模糊核聚类算法研究 [J ] . 通信学报 , 2015 , 36 ( 5 ): 74 - 80 .
YU X D , LEI Y J , YUE S H , et al . Research on PSO-based intuitionistic fuzzy kernel clustering algorithm [J ] . Journal on Communications , 2015 , 36 ( 5 ): 74 - 80 .
MERWE D W , ENGELBRECHT A P . Data clustering using particle swarm optimization [C ] // The 2003 Congress on Evolutionary Computation . 2003 , 1 : 215 - 220 .
TIWARI R , HUSAIN M , GUPTA S , et al . Improving ant colony optimization algorithm for data clustering [C ] // International Conference and Workshop on Emerging Trends in Technology , 2010 : 529 - 534 .
罗可 , 李莲 , 周博翔 . 基于变异精密搜索的蜂群聚类算法 [J ] . 控制与决策 , 2014 , 29 ( 5 ): 838 - 842 .
LUO K , LI L , ZHOU B X . Artificial bee colony rough clustering algorithm based on mutative precision search [J ] . Control and Decision , 2014 , 29 ( 5 ): 838 - 842 .
ALAM S , DOBBIE G , REHMAN S U . Analysis of particle swarm optimization based hierarchical data clustering approaches [C ] // Fifth International Conference on Soft Computing,Computing with Words and Perceptions in System Analysis,Decision and Control . 2015 : 1 - 4 .
王纵虎 , 刘志镜 , 陈东辉 . 一种改进的粒子群优化快速聚类算法 [J ] . 西安电子科技大学学报 , 2012 , 39 ( 5 ): 61 - 65 .
WANG Z H , LIU Z J , CHEN D H . Improved PSO-based fast clustering algorithm [J ] . Journal of Xidian University , 2012 , 39 ( 5 ): 61 - 65 .
高维尚 , 邵诚 , 高琴 . 群体智能优化中的虚拟碰撞:雨林算法 [J ] . 物理学报 , 2013 , 62 ( 19 ): 28 - 43 .
GAO W S , SHAO C , GAO Q . Pseudo-collision in swarm optimization algorithm and solution:rain forest algorithm [J ] . Acta Physica Sinica , 2013 , 62 ( 19 ): 28 - 43 .
SUN J , FENG B , XU W . Particle swarm optimization with particles having quantum behavior [C ] // Evolutionary Computation . 2004 : 1571 - 1580 .
SUN J , XU W , YE B . Quantum-behaved particle swarm optimization clustering algorithm [C ] // Advanced Data Mining and Applications . 2006 : 340 - 347 .
WANG M , FANG W , LI C . Clustering quantum-behaved particle swarm optimization algorithm for solving dynamic optimization problems [C ] // Bio-Inspired Computing-Theories and Applications . 2015 : 411 - 421 .
陈伟 , 傅毅 , 孙俊 , 等 . 一种改进二进制编码量子行为粒子群优化聚类算法 [J ] . 控制与决策 , 2011 , 26 ( 10 ): 1463 - 1468 .
CHEN W , FU Y , SUN J , et al . Improved vinery quantum-behaved particle swarm optimization clustering algorithm [J ] . Control and Decision , 2011 , 26 ( 10 ): 1463 - 1468 .
0
浏览量
208
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构