Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran.
Comput Methods Biomech Biomed Engin. 2024 Apr;27(5):651-679. doi: 10.1080/10255842.2023.2198628. Epub 2023 Apr 17.
The purpose of this article is to investigate the optimal control of nonlinear fractional order chaotic models of diabetes mellitus, human immunodeficiency virus, migraine and Parkinson's diseases using genetic algorithms and particle swarm optimization. Mathematical chaotic models of nonlinear fractional order type of the above diseases were presented. Then optimal control for each of the models and numerical simulation was done using genetic algorithm and particle swarm optimization algorithm. The results of the genetic algorithm method are excellent. All the results obtained for the particle swarm optimization method show that this method is also very successful and the results are very close to the genetic algorithm method. Very low values of MSE and RMSE errors indicate that the simulation is effective and efficient. Also, Lie symmetry was calculated for the proposed models and the results were presented.
本文旨在利用遗传算法和粒子群优化算法研究糖尿病、人类免疫缺陷病毒、偏头痛和帕金森病的非线性分数阶混沌模型的最优控制。给出了上述疾病的非线性分数阶数学混沌模型。然后，使用遗传算法和粒子群优化算法对每个模型进行了最优控制和数值模拟。遗传算法方法的结果非常出色。粒子群优化方法的所有结果都表明，该方法也非常成功，结果与遗传算法方法非常接近。MSE 和 RMSE 误差非常低表明模拟是有效和高效的。还计算了所提出模型的李对称，并给出了结果。
