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

• Datum: 2026
• Hauptverfasser: Tryhuba, A.M., Koval, N.Ya., Tryhuba, I.L., Firman, I.R., Famuliak, V.Yu.
• Format: Artikel
• Sprache: Ukrainisch
• Veröffentlicht: PROBLEMS IN PROGRAMMING 2026
• Schlagworte: 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
• Online Zugang: 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...