Novel model of particle swarm optimization for data mining based on improved ant colony algorithm

Chunxia Wang

Abstract

The biggest characteristic of the particle swarm algorithm is simple, easy to understand, and has a few parameters, easy to implement. This paper mainly introduces the basic thought of ant colony algorithm, and the improved algorithm according to the actual need. Ant colony algorithm will search behavior of ants to can improve 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 algorithm. Experimental results show that the improved ant colony algorithm can effectively improve the efficiency of data mining in particle swarm.