Aimed at the problem of low parameter identification accuracy of chaotic systems,a multi-strategy improved whale optimization algorithm(MIWOA)is proposed based on the whale optimization algorithm(WOA).MIWOA uses Chebyshev chaotic mapping to select high-quality initial populations,and nonlinear convergence factor and adaptive weight to improve the convergence speed of the algorithm.In order to avoid falling into local optimal solution,MI-WOA dynamically selects adaptive t distribution or ant lion optimization algorithm to update the later position and im-prove the ability to handle local extremum.Through simulation experiments on 10 benchmark functions and high-di-mensional test functions,it is shown that MIWOA has good stability and convergence accuracy.Applying MIWOA to identify the parameters of Rössler and Lü chaotic systems,the simulation results are superior to existing achievements,indicating the efficiency and practicality of MIWOA in identifying chaotic system parameters in this paper.
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