Solving the problem of mathematical models overparameterization for some nonlinear oscillating systems

V. Gorodetskyi, M. Osadchuk
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引用次数: 1

Abstract

This study proposes a numerical-analytical method that allows us to simplify the model, which is obtained on the basis of the single observable variable of an object under the study, and which may be overparameterized. As a model, we consider a system of ordinary differential equations with polynomial right-hand sides. To solve this problem, the so-called differential model is used, that is, a system in which unknown variables are replaced by derivatives of the observed variable, and which is derived on the basis of a system under the study so that the observed variables of these systems coincide. The method of simplification of a system under the study is based on the fact that using a numerical method, a simpler differential model can be obtained. Next, an analytical transition from a simplified differential model to a simplified original system is performed. In this case, the time series error remains within given limits even for systems with deterministic chaos, despite their high sensitivity to the initial conditions.
求解非线性振荡系统数学模型的过参数化问题
本研究提出了一种数值解析方法,使我们能够简化模型,该模型是基于研究对象的单个可观测变量获得的,并且可能被过度参数化。作为一个模型,我们考虑一个右手边为多项式的常微分方程组。为了解决这个问题,我们使用了所谓的微分模型,即在一个系统中,用观测变量的导数代替未知变量,并在研究的系统的基础上推导出这些系统的观测变量重合。所研究的系统简化方法是基于这样一个事实,即使用数值方法可以得到一个更简单的微分模型。接下来,从简化的微分模型到简化的原始系统进行解析转换。在这种情况下,即使对于具有确定性混沌的系统,尽管它们对初始条件具有很高的灵敏度,但时间序列误差仍然在给定的范围内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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