Application and Adaptation of Data Mining for Innovative Crisis Management of Transport and Logistics Enterprises Under Environmental Turbulence and Systemic Risk (within the WARMI Paradigm)

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Published: 06.09.2026

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Krasnyuk Maxim
Kyiv National Economic University named after Vadym Hetman

Abstract

The article explores the features and specifics of the application of Data Mining technologies in innovative anti-crisis management by transport and logistics companies in the service sector under the WARMI paradigm. The key areas of use of intelligent data analysis are identified: forecasting, anomaly detection, classification, clustering and early detection of crisis signals. The need for integrating Data Mining with Big Data, machine learning and mathematical optimization for the formation of a proactive and adaptive anti-crisis management system is substantiated.

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Data Availability Statement

All data supporting the findings of this study are presented in the text of the scientific work.

Issue

No. 308 (2026): 8th ISPC «Progressive Science and Achievements» (September 6-8, 2026; Dallas, USA).

Section

Information and Web technologies
Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Biography

Krasnyuk Maxim, Kyiv National Economic University named after Vadym Hetman

Associate Professor, Department of Computer Science

How to Cite

Krasnyuk, M. (2026). Application and Adaptation of Data Mining for Innovative Crisis Management of Transport and Logistics Enterprises Under Environmental Turbulence and Systemic Risk (within the WARMI Paradigm). Scientific Collection «InterConf», 308, 123–130. https://interconf.openpubarchive.com/index.php/proceeding/article/view/86

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