Quantum Immune Evolutionary Algorithm with Application in Clustering

摘要

A quantum immune evolutionary algorithm is proposed to solve clustering problem. In this algorithm, the rotation angle is determined by comparing the probability expectation corresponding to quantum chromosome with the best solution, the idea of the clonal proliferation is introduced into the collapse operation to obtain better solutions, different quantum chromosome evolves with different speeds to implement the exploration and exploitation, He gate is used to prevent the premature convergence. Finally, we apply this algorithm to clustering problem and compare its performance with conventional genetic algorithm and quantum evolutionary algorithm, the experimental results illustrate that the proposed algorithm has better performance.