In this paper, a new learning algorithm called dynamic echo state network(DESN) is proposed to solve the problem that ESN algorithm adjusts only output weight in the process of training. In order to improve nonlinear mapping capability of Sigmoid activation function, the mapping range factor is introduced into activation function, it not only adjusts position and figure of activation function, but also adjusts mapping range. Simulation results verified the effectiveness and feasibility of this method by using some real-world datasets. And it is applied to develop a prediction model for the surface-to-air missile survivability, and the result was satisfied.