Abstract
This research effort has two main orientations. The first is the sensitivity analysis performance of the parameters that are considered to influence the problem of forest fires. This is conducted by the Pearson’s correlation analysis for each factor separately. The second target is the development of an intelligent fuzzy (Rule Based) Inference System that performs ranking of the Greek forest departments in accordance to their degree of forest fire risk. The system uses fuzzy algebra in order to categorize each forest department as “risky” or “non-risky”. The Rule Based system was built under the MATLAB Fuzzy integrated environment and the sensitivity analysis was conducted by using SPSS.
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Tsataltzinos, T., Iliadis, L., Stefanos, S. (2009). Sensitivity Analysis of Forest Fire Risk Factors and Development of a Corresponding Fuzzy Inference System: The Case of Greece. 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_29
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DOI: https://doi.org/10.1007/978-3-642-03969-0_29
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