7 papers
Aerial Wildfire Suppression Planning with a Hybrid CNN-Cellular Automata Fire Model
Ion Matei, Maksym Zhenirovskyy, Takuya Kurihana +2
Aerial wildfire suppression requires not only predicting fire spread, but also designing effective intervention strategies under operational and environmental uncertainty. We prese…
Neural-Parameterized Cellular Automata for Wildfire Spread
Maksym Zhenirovskyy, Ion Matei, Rohit Vuppala +2
Traditional wildfire models rely on rigid, low-dimensional parameters and static fuel maps, frequently underpredicting fire spread. To address this weakness, we introduce a hybrid…
Differentiable Parameter Optimization for DAEs with State-Dependent Events
Ion Matei, Maksym Zhenirovskyy, Anthony Wong
Differential-algebraic equations (DAEs) with state-dependent events arise in systems whose continuous dynamics are constrained by algebraic equations and interrupted by mode change…
Automated BPMN Model Generation from Textual Process Descriptions: A Multi-Stage LLM-Driven Approach
Ion Matei, Maksym Zhenirovskyy, Praveen Kumar Menaka Sekar +1
Automatically reconstructing BPMN models from unstructured natural-language descriptions remains challenging due to heterogeneous modeling conventions, multilingual sources, and th…
Resilience Quantification and its Support for Operational Resilience
Ion Matei, Maksym Zhenirovskyy
We present a method to quantify a system's resilience capacity, i.e., the set of degradation magnitudes for which all functional requirements remain satisfied. These requirements c…
Ambiguity Detection and Elimination in Automated Executable Process Modeling
Ion Matei, Praveen Kumar Menaka Sekar, Maksym Zhenirovskyy +4
Automated generation of executable Business Process Model and Notation (BPMN) models from natural-language specifications is increasingly enabled by large language models. However,…