A Fuzzy Decision Support System Evaluating Qualitative Attributes towards Forest Fire Risk Estimation

This paper aims in the design and development of a Decision Support System performing forest fire risk estimation of forest departments in Greece. The system applies a Fuzzy Logic model that considers a variety of independent variables. This approach takes into consideration the center of gravity of every independent variable, in order to produce various scenarios, having the advantage of evaluating different kind of data. It can also evaluate the human experience in order to estimate the degree of forest fire risk, caused by each involved factor. In this way proper Fuzzy Sets are produced. Finally Partial Risk Indices are produced that express the degree of forest fire risk due to each involved parameter separately. Each department is assigned many Partial Risk Indices which are unified (under different perspectives) using Fuzzy conjunction operators (T-Norms). This is done towards the production of a Unified Forest Fire Risk Index for each area.