Architecture of a software system for multi-model ecological risk forecasting for digital management of municipal organic waste

• Опубліковано в: PROBLEMS IN PROGRAMMING
• Дата: 2026
• Випуск: 1
• Сторінки: 25-39
• ISSN: 1727-4907
• Автори та афіліації: A.M. Tryhuba — Lviv National University of Veterinary Medicine and Biotechnology named after S. Gzhytsky; N.Ya. Koval — Lviv State University of Life Safety; I.L. Tryhuba — Lviv National University of Veterinary Medicine and Biotechnology named after S. Gzhytsky; I.R. Firman — Lviv State University of Life Safety — ORCID: 0009-0005-5840-9815; V.Yu. Famuliak — Lviv National University of Veterinary Medicine and Biotechnology named after S. Gzhytsky
• Автори: Tryhuba, A.M., Koval, N.Ya., Tryhuba, I.L., Firman, I.R., Famuliak, V.Yu.
• Формат: Стаття
• Мова: Українська
• Опубліковано: PROBLEMS IN PROGRAMMING 2026
• Теми: ecological risk; multi-model forecasting; municipal organic waste; machine learning; Random Forest; Gradient Boosting; XGBoost; UML architecture; permutation importance; digital management; information system; decision support; UDC 004.94:628.4:504.064
• Онлайн доступ: https://pp.isofts.kiev.ua/index.php/ojs1/article/view/889
• Назва журналу: Problems in programming

The article investigates the problem of designing a software system for multi-model ecological risk forecasting for digital management of municipal organic waste under conditions of increasing volumes of significant data and the need for prompt decision-making at the local level. An analysis of mode...