Methodological support of the expert system in the problem of interaction of business ecosystems

K. Simonov, V. Kuimov, M. V. Kobalinsky, S. V. Kirillova, A. Zotin, M. Kurako, A. Matsulev
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Abstract

The paper discusses modern approaches and digital transformations in business models and interactions. In this regard for a quantitative description of interactions in ecosystems a variant of methodological support based on neural networks is proposed for fast nonlinear multiparametric regression of large data sets within the projected expert system. The possibility of effective solution of the problem of filling gaps in the observational data arrays and processing of not precisely specified information is shown. This approach is proposed for solving predictive problems in the problem of interaction of objects of interest in business ecosystems. The article was prepared within the framework of the Grant of the RFBR and the Government of the Krasnoyarsk Territory No. 20-410-242916 / 20 r_mk Krasnoyarsk.
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专家系统在商业生态系统交互问题上的方法论支持
本文讨论了商业模式和交互中的现代方法和数字化转型。在这方面,对于生态系统中相互作用的定量描述,提出了一种基于神经网络的方法支持变体,用于预测专家系统内大型数据集的快速非线性多参数回归。指出了有效解决观测数据阵列中空白的填补和未精确指定信息处理问题的可能性。该方法是为解决商业生态系统中感兴趣对象交互问题中的预测问题而提出的。这一条款是在第20-410-242916 / 20 r_mk克拉斯诺亚尔斯克号联邦联邦调查局和克拉斯诺亚尔斯克地区政府的赠款框架内编写的。
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