Abstract
This paper presents the design of a fuzzy algebra model and the implementation of its corresponding Intelligent System (IS). The System is capable of estimating the risk due to extreme disaster phenomena and especially due to natural hazards. Based on the considered risk parameters, an equal number of fuzzy sets are defined. For all of the defined fuzzy sets trapezoidal membership functions are used for the production of the partial risk indices. The fuzzy sets are aggregated to a single one that encapsulates the overall degree of risk. The aggregation operation is performed in several different ways by using various Fuzzy Relations. The degree of membership of each case to an aggregated fuzzy set is the final overall degree of risk. The IS has been applied in the problem of torrential risk estimation, with data from river Evros. The compatibility of the system to existing models has been tested and also the results obtained by two distinct fuzzy approaches have been compared.
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Iliadis, L.S., Spartalis, S. (2009). Intelligent Fuzzy Reasoning for Flood Risk Estimation in River Evros. In: Palmer-Brown, D., Draganova, C., Pimenidis, E., Mouratidis, H. (eds) Engineering Applications of Neural Networks. EANN 2009. Communications in Computer and Information Science, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03969-0_6
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DOI: https://doi.org/10.1007/978-3-642-03969-0_6
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