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| a real-valued quantum genetic niching clustering algorithm and its application to color image segmentation | |
| Chang Dongxia; Zhao Yao; Zheng Changwen | |
| 2011 | |
| Conference Name | 2011 IEEE International conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011 |
| Source | Proceedings - 2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011 |
| Pages | 144-147 |
| Conference Date | December 14, 2011 - December 17, 2011 |
| Conference Place | Wuhan, Hubei, China |
| Indexed Type | EI |
| ISBN | 9780769546230 |
| Department | (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 |
| English Abstract | 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. |
| Keyword | Image Segmentation Quantum Computers Quantum Optics |
| Sponsorship | IEEE Tainan Section; Huazhong University of Science and Technology; National Cheng Kung University |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/16303 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation 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. |
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