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Title: | Modeling the development of fire unconventional methodology |
Author: | Blahová, Marta; Hromada, Martin |
Document type: | Conference paper (English) |
Source document: | Proceedings - 25th International Conference on Circuits, Systems, Communications and Computers, CSCC 2021. 2021, p. 116-119 |
ISBN: | 978-1-66542-749-4 |
DOI: | https://doi.org/10.1109/CSCC53858.2021.00028 |
Abstract: | The article describes a proposal for a different approach to modeling the development of fire using multiagent systems and evaluating its benefits. One of the chapters lists the disadvantages that such an approach provides compared to currently used "conventional" models. Modeling and simulation is essential for understanding complex ecological systems. How-ever, knowledge of the structure and behavior of these systems is limited, and models must be revised frequently as our understanding of a system improves. Moreover, the dynamic, spatial distribution of activity in very large systems necessitates mapping natural mecha-nisms as logically as possible onto computer structures. Modeling and simulations are essential for understanding complex ecological systems. How-The knowledge structure and behavior of these systems is limited and models must be it will often be revised as our understanding of the system is prepared. In addition, the dynamic, spatial distribution of activity in very large systems involving the mapping of natural mechanic-logic into computer structures. This article describes the theoretical and algorithmic tools for creating component-based models and simulating dynamic bath phenomena. These methods focus on irregular distribution activity in ecological processes. This approach to event-based modeling naturally leads to efficient simulation algorithms. Ecological modeling benefits from these efficient simulation algorithms and the reuse of basic model components. The method is based on the event it is demonstrated on the physical model of fire propagation. |
Full text: | https://ieeexplore.ieee.org/document/9668331 |
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