In this paper, a comparison between the experimental values for the kinetics of the fast redox reaction between Cu 2+ and S 2 O 3 2− and some possible variants of analogical modeling and numerical simulation for this pre-equilibrium reaction have been presented. One of them is based on a function with a periodical, strongly under-damped component. For a non-periodical fast damped evolution of reaction between Cu 2+ and S 2 O 3 2− , this paper proposes a variant of numerical modeling and simulation based on two exponential functions. For this complex reaction kinetics, the proposed approach based on application of neural networks is an efficient and accurate tool to solve modeling problems. The method ensures a good approximation of the experimental data, with a remarkable flexibility of analyses and synthesis as elaborated in the paper. The associated numerical simulation operates with an easy and flexible program, which allows the change in large limits of some structure parameters, for the adaptation of the numerical results with the experimental measurements.

中文翻译：

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Cu2+ 与 S2O3 2− 在水溶液中的快速相互作用

在本文中，比较了 Cu 2+ 和 S 2 O 3 2- 之间快速氧化还原反应动力学的实验值，以及该预平衡反应的类比建模和数值模拟的一些可能变体。其中之一是基于具有周期性、强欠阻尼分量的函数。对于Cu 2+ 和S 2 O 3 2- 之间反应的非周期性快速阻尼演化，本文提出了一种基于两个指数函数的数值建模和模拟的变体。对于这种复杂的反应动力学，所提出的基于神经网络应用的方法是解决建模问题的有效而准确的工具。该方法确保了实验数据的良好近似，具有论文中详述的分析和合成的显着灵活性。