Fundamental fuzzy relation concepts of a DSS for the estimation of natural disasters' risk (The case of a trapezoidal membership function)

The effective protection from natural disasters requires the development of a rational and sensible protection and prevention policy. This project deals with the development and testing of a decision support system that acts on two levels. On the first level, it estimates the annual forest fire risk for each area of Greece using a fuzzy Trapezoidal membership function. Reference is done to past work in this area and past results of forest fire risk estimation (using other models) were compared to the results of this system. On the second level, it forecasts a narrow expected closed interval for the burned area, using a fuzzy expected interval model. It is the first time that such forecasts are produced and such results are obtained. Physically and operationally, the decision support system consists of two parts. The risk estimation part is more straightforward and it was developed in MS-Access in order to have the ability to store and use a vast amount of data. The forecasting part was developed in a decision support system shell, in order to have a sound Inference mechanism. (c) 2005 Elsevier Ltd. All rights reserved.