Novel model of particle swarm optimization for data mining based on improved ant colony algorithm
Wang Chun-xia · 2014
The biggest characteristic of the particle swarm al gorithm is simple, easy to understand, and has a fe w parameters, easy to implement. This paper mainly introduces the basic thought of ant colony algorithm, and the imp roved algorithm according to the actual need. Ant colony algorithm will search behavior of ants to can impro ve the quality of solution and convergence speed near the optimal solution, thus improving algorithm performance. The paper present novel model of Particle swarm optimization for data mining based on improved ant colony algori thm. Experimental results show that the improved ant col ony algorithm can effectively improve the efficienc y of data mining in particle swarm.