A novel swarm intelligence optimization AC_ICPSO(ant colony and immune clone particle swarm optimization)algorithm is proposed.It combines ACO(ant colony optimization)and PSO(particle swarm optimization)to conduct dynamic swarm query.According to introducing crossover and mutation operator

encoding repeatedly

iterative choice

etc.

it leads to widen data range

improves search precision and convergence efficiency

avoids premature convergence

and reduces complexity of the conventional ACO or PSO algorithm.Then AC_ ICPSO is used to optimize the parameters of LSSVM(least square support vector machines)to predict the melt index of polypropylene

so the best model AC_ICPSO_LSSVM is obtained.The detailed researches on the optimized model are carried out based on the data from a real plant

and the result shows that the proposed approach has great prediction accuracy and effectiveness.