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  1 - Lorenz hyper chaotic system parameter estimation using improved whale optimization algorithm with Tabu Search
  Mahsa Esmaeilnia Mostafa Saadatifar Mahdi Yaghoobi
  Lorenz hyper chaotic system parameter estimation using improved whale optimization algorithm with Tabu Search Chaotic systems are very complex dynamic systems that have some special characteristics such as high sensitivity to initial conditions, lack of statistical pre More

  Lorenz hyper chaotic system parameter estimation using improved whale optimization algorithm with Tabu Search Chaotic systems are very complex dynamic systems that have some special characteristics such as high sensitivity to initial conditions, lack of statistical prediction, and despite seemingly random behavior, chaotic systems are completely deterministic. Estimation of parameters of super-chaotic oscillators is one of the most important issues in the field of chaos. Parameter estimation of hyper-chaotic systems can be considered as a multivariate optimization problem. This article aims to present a new method for estimating the parameters of the superchaotic Lorenz system based on the improvement of the whale algorithm with the forbidden search algorithm. The simulation results show that the whale algorithm has a high competitive power compared to similar meta-heuristic algorithms. Estimation of parameters of super-chaotic oscillators is one of the most important issues in the field of chaos. Parameter estimation of hyper-chaotic systems can be considered as a multivariate optimization problem. This article aims to present a new method for estimating the parameters of the superchaotic Lorenz system based on the improvement of the whale algorithm with the forbidden search algorithm. The simulation results show that the whale algorithm has a high competitive power compared to similar meta-heuristic algorithms. Manuscript profile