Nonlinear Parameter Estimation Based on Average Information Differential Evolution Algorithm
Liao Fen · Shuxue de shijian yu renshi · 2013
We proposed an average information differential evolution(AIDE) based on the idea of multiple population collaboration and the information sharing machnism from average information particle swarm optimization.Compared with tranditional DE,AIDE has the advantage as follows,firstly,AIDE has novel mutation operator which made the individuals have the characteristics of global consciousness when mutation;secondly,we designed three mutation operator for AIDE,which overcomes the oneness of mutation.Prom the view of algorithm structure,the new algorithm has fewer parameters and easy to realize;from the respect of experment results,AIDE needs fewer iteration times,smaller population scale,and the numerical results betters then other swarm intelligence optimization,these details indicated that the improvement of AIDE are feasible and effective,which could be applied in the field of nonlinear parameter estimation widely.