An effective method for construction of fuzzy classification system（ FCS） is proposed. In FCS

the initial fuzzy rules are optimized with a quantum bit which has many unique advantages such as small population size

fast convergence

short training time and strong global search ability. After then

in order to accomplish the optimization for the fuzzy classification space and reduce number of fuzzy rules

quantum-behaved particle swarm optimization（QPSO）algorithm is proposed to improve characteristics of initial FCS. The experimental result demonstrates that this method is more efficient and accurate than other methods without QPSO.