a real-valued quantum genetic niching clustering algorithm and its application to color image segmentation

ISCAS OpenIR

	a real-valued quantum genetic niching clustering algorithm and its application to color image segmentation
	Chang Dongxia; Zhao Yao; Zheng Changwen
	2011
会议名称	2011 IEEE International conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011
会议录名称	Proceedings - 2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011
页码	144-147
会议日期	December 14, 2011 - December 17, 2011
会议地点	Wuhan, Hubei, China
收录类别	EI
ISBN	9780769546230
部门归属	(1) Institute of Information Science Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing 100044 China; (2) National Key Lab. of Integrated Information System Technology Institute of Software Chinese Academy of Sciences Beijing 100080 China
摘要	This paper proposes a novel genetic clustering algorithm, called a real-valued quantum genetic niching clustering algorithm (RQGN), which is based on the concept and principles of quantum computing, such as the qubits and superposition of states. Our algorithm can automatically clustering a data set into clusters without the need to know the number of clusters in advance. A dynamic identification of the niches is performed at each generation to automatically evolve the optimal number of clusters as well as the cluster centers of the data set. After getting the niches of the population, a Q-gate with adaptive selection of the angle for every niches is introduced as a variation operator to drive individuals toward better solutions. The experimental results show that RQGN algorithm has high performance, effectiveness and flexibility. © 2011 IEEE.; This paper proposes a novel genetic clustering algorithm, called a real-valued quantum genetic niching clustering algorithm (RQGN), which is based on the concept and principles of quantum computing, such as the qubits and superposition of states. Our algorithm can automatically clustering a data set into clusters without the need to know the number of clusters in advance. A dynamic identification of the niches is performed at each generation to automatically evolve the optimal number of clusters as well as the cluster centers of the data set. After getting the niches of the population, a Q-gate with adaptive selection of the angle for every niches is introduced as a variation operator to drive individuals toward better solutions. The experimental results show that RQGN algorithm has high performance, effectiveness and flexibility. © 2011 IEEE.
关键词	Image Segmentation Quantum Computers Quantum Optics
主办者	IEEE Tainan Section; Huazhong University of Science and Technology; National Cheng Kung University
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16303
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Chang Dongxia,Zhao Yao,Zheng Changwen. a real-valued quantum genetic niching clustering algorithm and its application to color image segmentation[C],2011:144-147.