Attribute Reduction Algorithm Based on MQPSO Optimization

A quantum particle swarm optimization algorithm with mutation operator (MQPSO) can improve the global search capability to avoid local optimum by introducing the mutation mechanism into the quantum particle swarm optimization (QPSO). In this paper, an attribute reduction method based on MQPSO optimization is proposed, and a strategy of iterative record is given to modify the timeconsuming part of the algorithm such that the time complexity can be reduced.