Innovative Solutions for Forecasting the Sustainable Growth of the Russian Confectionery Industry Based on the Cognitive Model

In modern conditions, ensuring companies’ sustainable development is of great importance. The financial stability of partner enterprises largely determines the sustainable development of the company. Despite the large number of scientific works in this area, gaps exist that require additional scientific research to eliminate. The relevance of the study is that in modern conditions, AI techniques are used to ensure companies’ sustainability. The scientific novelty lies in the fact that the study proposes and proves the hypothesis that a company’s profit forecast can be obtained using an AI system, and then a strategic partner company in the confectionery industry can be selected using the fuzzy model. The purpose of this study is to form a deep learning model "Random Forest" (DF) based on data collected by a parser from company websites, add parameters calculated using the VaR, Z-Altman, and Hurwitz models to the dataset, and form a fuzzy classifier model for decision-making. The study is based on the following methods: a cognitive model that includes modules that calculate the VaR, Z-Altman, and Hurwitz parameters, as well as the DF deep learning model and the fuzzy model. The authors proposed a methodology based on the fuzzy classifier model for assessing the reliability of a partner. The Fuzzy model uses the following parameters: return on equity (ROE) and return on sales (ROS). Both indicators are calculated using the predicted value of net profit returned by the DL model.

AI-model; Banking system; Cognitive model; Deep learning model; Random forest

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