Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: 13th Computer Science Online Conference "Artificial Intelligence Algorithm Design for Systems" (CSOC 2024); Zlin, Czech Republic; Zlin, Czech Republic

Год издания: 2024

Идентификатор DOI: 10.1007/978-3-031-70518-2_9

Ключевые слова: machine learning, Hierarchical framework, economic performance, bankruptcy prediction, financial health

Аннотация: The article discusses important aspects of bankruptcy prediction, including early risk detection and informed financial decision making. An automated decision tree learning method can efficiently analyze multiple economic indicators, automatically identify key factors, and thus improve the accuracy and interpretability of predictioПоказать полностьюns. This research approach can be a valuable tool for investors, lenders and managers, helping them to reduce financial risks and ensure the financial stability of companies. The article aims to expand the understanding of the impact of economic factors on bankruptcy and to propose innovative methods for analyzing data to make informed decisions.

Журнал: Artificial Intelligence Algorithm Design for Systems

Номера страниц: 88-98

Место издания: Zlin

• Kravtsov Kirill I. (Reshetnev Siberian State University of Science and Technology)
• Kukartsev Vladislav V. (Bauman Moscow State Technical University)
• Nelyub Vladimir A. (Bauman Moscow State Technical University)
• Borodulin Aleksey S. (Bauman Moscow State Technical University)
• Suprun Elena V. (Reshetnev Siberian State University of Science and Technology)

• Ядро РИНЦ (eLIBRARY.RU)