论文标题

重叠的世代模型中的预测和控制:通过人工智能稳定混乱

Forecasting and control in overlapping generations model: chaos stabilization via artificial intelligence

论文作者

Alexeeva, T. A., Diep, Q. B., Kuznetsov, N. V., Mokaev, T. N., Zelinka, I.

论文摘要

不规则,尤其是混乱的行为通常对经济过程不受欢迎,因为它给预测其动态带来了挑战。在这种情况下,通过其数学模型对这种过程的控制可以用来抑制混乱的行为,并将系统从不规则的动力学转移到常规动力学。 在本文中,我们构建了一个具有控制功能的重叠的世代模型。通过应用进化算法,我们表明,在没有对照的情况下,可以在此模型中观察到规则和不规则行为(周期性和混乱)。然后,我们使用Pyragas控制方法与两个控制参数的控制合成来解决控制模型不规则行为的问题。我们解决了应用进化算法来选择控制参数的许多优化问题,以确保周期性轨道的稳定性。我们比较了应用控制之前和之后模型动力学的定性和定量特征,并验证了使用仿真获得的结果。 因此,我们证明了与Pyragas控制方法相结合的人工智能技术(特别是进化算法)非常适合在本文中考虑的模型中深入分析和稳定不规则动力学。

Irregular, especially chaotic, behavior is often undesirable for economic processes because it presents challenges for predicting their dynamics. In this situation, control of such a process by its mathematical model can be used to suppress chaotic behavior and to transit the system from irregular to regular dynamics. In this paper, we have constructed an overlapping generations model with a control function. By applying evolutionary algorithms we showed that in the absence of control, both regular and irregular behavior (periodic and chaotic) could be observed in this model. We then used the synthesis of control by the Pyragas control method with two control parameters to solve the problem of controlling the irregular behavior of the model. We solved a number of optimization problems applying evolutionary algorithms to select control parameters in order to ensure stability of periodic orbits. We compared qualitative and quantitative characteristics of the model's dynamics before and after applying control and verified the results obtained using simulation. We thus demonstrated that artificial intelligence technologies (in particular, evolutionary algorithms) combined with the Pyragas control method are well suited for in-depth analysis and stabilization of irregular dynamics in the model considered in this paper.

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