This paper introduces the "Absorbing Walls" and the multi-phase theory to improve Quantum-behaved Particle Swarm Optimization algorithm and applies it to solve complex problem of classification. In the process of classification, the double fitness functions are used to increase the precise of classification rules got. The result of experimentation shows that not only the efficiency of this improved optimization algorithm is increased, but...
