Parameters Estimation in Lotka-Volterra Models Based on Artificial Immune Network Algorithm

This paper is concerned with the parameter identification problem for lotka-volterra systems. An artificial immune network algorithm(aiNet), which is a novel evolutionary computation technique, is proposed to solve this problem. The feasibility of this approach is demonstrated through identifying the parameters. The performance of the proposed aiNet is compared with Esposito W.R. methods in terms of parameter accuracy. It is illustrated in simulations fitted curve and square error that the proposed aiNet is more successful than Esposito W.R.