Considering the issues of premature convergence and low solution accuracy in solving high-dimensional problems with the basic chickenswarmoptimizationalgorithm, an adaptivesimplifiedchickenswarmoptimization alg...
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Considering the issues of premature convergence and low solution accuracy in solving high-dimensional problems with the basic chickenswarmoptimizationalgorithm, an adaptive simplified chicken swarm optimization algorithm based on inverted S-shaped inertia weight(ASCSO-S) is proposed. Firstly, a simplifiedchickenswarmoptimizationalgorithm is presented by removing all the chicks from the chickenswarm. Secondly, an inverted S-shaped inertia weight is designed and introduced into the updating process of the roosters and hens to dynamically adjust their moving step size and thus to improve the convergence speed and solution accuracy of the algorithm. Thirdly, in order to enhance the exploration ability of the algorithm, an adaptive updating strategy is added to the updating process of the *** experiments on 21 classical test functions show that ASCSO-S is superior to the other comparison algorithms in terms of convergence speed, solution accuracy, and solution stability. In addition, ASCSO-S is applied to the parameter estimation of Richards model, and the test results indicate that ASCSO-S has the best fitting results compared with other three algorithms.
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