Instead of the traditional state transition matrix eigenvalue estimation methods

the convergence rate estimation of real coded artificial immune algorithm(RCAIA) is studied based on the stochastic processes theory.The method begins with analyzing the necessary condition for probability-based strong convergence of artificial immune algorithm and takes it as the sufficient condition of a class of RCAIA

and the probability-based strong convergence exponential rate estimation method of RCAIA is proposed.The final convergence of the best antibody is taken as convergence judgment

which can overcome the conservative defect of traditional estimation methods.The method can be used to analyze the convergence and convergence rate of a class of artificial immune algorithms.The research can be used to optimize the convergence rate in the practical application of artificial immune algorithms.