Situational Assessment of Wildfires: a Fuzzy Spatial Approach
Résumé
Decision support systems coupled with a Geographic Information System (GIS) are useful for assessing spatialized risks, which can be either natural, industrial or even anthropic. However, when the knowledge is not sufficiently precise or when the processes are complex, the methods of analysis of the GIS are not always sufficient.
In this article, we propose to couple a GIS with a Fuzzy Expert System capable of evaluating fuzzy spatial rules, that is to say, fuzzy rules integrating spatial relations or properties. These are based on fuzzy mathematical morphology and model high-level metric or topological relationships such as “being close to”, “being in the direction of” or “being adjacent to”. The proposed approach has been applied to the identification of risky issues in the case of wildfires. We detail the expert knowledge modeled and show the results obtained in a graphic interface dedicated to the intervention of firefighters.
Mots clés
artificial intelligence
fuzzy logic
machine learning
online learning
Decision support system
Geographic Information System
spatialized risk assessment
Fuzzy Expert System
ExpressIF
fuzzy spatial rules
Fuzzy spatial relations
spatial properties
fuzzy mathematical morphology
high-level metric
topological relationships
wildfire
graphic interface
firefighter
Measurement
Graphics
Morphology
Fires
Tools
Mathematical model
vulnerability assessment
situational assessment
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