<FONT face=Verdana>In immune clonal selection algorithms

global convergence ability is worse if clonal selection is only adopted. However

immune algorithm with (μ+λ) selection is easy to fall into premature convergence. In order to ensure the exploitation and exploration

an adaptive immune clonal selection cultural algorithm is proposed. Dual structure of cultural algorithm is adopted in the algorithm. And a hybrid selection strategy integrating (μ+λ) selection and clonal selection is put forward. The proportion of population influenced by each selection method is adaptively adjusted according to implicit knowledge extracted from the evolution process. Aiming at benchmark functions

simulation results indicate that the algorithms can effectively improve the speed of convergence and have better computation stability.