Adaptive Simulation of Separate Factors in the Alexandridis Wildfire Model

Isabella Papageorgiou, Nuno Fachada, Markos Avlonitis, Joao P. Matos-Carvalho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper provides a concise and comprehensive analysis of forest fire spread simulation. The Alexandridis model was implemented and enhanced utilizing stochastic methods in a Python environment. The impact of various factors influencing fire spread was individually studied. Results were empirically analyzed based on model-generated images, addressing the lack of real fire data. Multiple scenarios and parameter values were explored, highlighting the effectiveness of the developed method. In summary, this paper provides a concise and comprehensive analysis of forest fire spread simulation, demonstrating the efficacy of the Alexandridis model. Findings suggest the potential for developing a more effective model to combat forest fires and improve prediction and prevention methods.

Original languageEnglish
Title of host publicationProceedings - 8th International Young Engineers Forum on Electrical and Computer Engineering, YEF-ECE 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages31-38
Number of pages8
ISBN (Electronic)9798350387643
DOIs
Publication statusPublished - 5 Jul 2024
Event8th International Young Engineers Forum on Electrical and Computer Engineering, YEF-ECE 2024 - Lisbon, Portugal
Duration: 5 Jul 2024 → …

Publication series

Name2024 8th International Young Engineers Forum on Electrical and Computer Engineering (YEF-ECE)

Conference

Conference8th International Young Engineers Forum on Electrical and Computer Engineering, YEF-ECE 2024
Country/TerritoryPortugal
CityLisbon
Period5/07/24 → …

Keywords

  • cellular automata
  • forest-fire
  • simulation
  • stochastic model

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