CONCEPTUAL MODEL OF INTELLIGENT ASSESSMENT OF CONSEQUENCES OF TECHNOGENIC CATASTROPHES - LIPIANINA-HONCHARENKO, KHRYSTYNA; KOMAR, MYROSLAV; YURKIV, KHRYSTYNA; LUKIANCHUK, VASYL (Herald of Khmelnytskyi National University. Technical sciences, 2023)
In the context of modern warfare, the relevance of technogenic safety becomes particularly crucial due to the increasing threat of technogenic disasters. This article is dedicated to studying the most current challenges related to technogenic safety during wartime and determining the necessity for the development of novel approaches for prevention and management of the consequences of such catastrophes. The research object encompasses a complex of issues associated with mitigating the aftermath of technogenic disasters, while the main goal is the development of a model for intelligent assessment of these consequences. The aim of the work lies in devising a conceptual model for the intelligent assessment of the aftermath of technogenic catastrophes. To achieve this goal, the following tasks were undertaken: data collection regarding technogenic disasters, analysis of this data, development of a model for predicting consequences, determination of influencing parameters, and formulation of recommendations. The obtained results underscore the importance of creating such a model for swift and effective determination of the danger level in case of technogenic catastrophes. The conceptual model is built on the foundation of data collection, analysis, consequences modeling, and assessment, which allows for the consideration of diverse aspects of catastrophes and their impact on the environment and human beings. Evaluation results of the model demonstrated its effectiveness in classification and forecasting of danger levels. The achieved accuracy surpasses 77%, thus confirming the success of the approach. In the future, the model is intended to be expanded by considering additional factors, such as weather conditions and sensor readings, and applied across various fields of activity where operational assessment of danger levels is crucial. In conclusion, the article is dedicated to the development of a conceptual model for intelligent assessment of the consequences of technogenic catastrophes, which utilizes data, analysis, and modeling to swiftly and accurately determine danger levels, thereby enhancing safety in emergency situations.