A Real-Valued Quantum Genetic Niching Clustering Algorithm and its Application to Color Image Segmentation
Dongxia Chang, Yao Zhao, Changwen Zheng · 2011
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.