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Monday, July 31, 2017

Hybrid intelligent modeling of wild fires risk

Abstract

Forest fires are one of the most serious natural disasters for the countries of the Mediterranean basin and especially for Greece. Studying the climate change effect on the maximization of the problem is a constant objective of the scientific community. This research initially proposes an innovative hybrid version of the statistical Chi-Square test that employs Soft Computing methods. More specifically it introduces the Fuzzy Chi Square Independence test that fuzzifies p values using proper Risk Linguistics, based on Fuzzy Membership functions. In the second stage, it proposes a new Hybrid approach that models the evolution of burned areas in Greece. First it analyzes the parameters and determines the way they affect the problem, by constructing Fuzzy cognitive maps. The system projects into the future and forecasts the evolution of the problem through the years till 2100, based on the variance of average monthly temperature and average rain height (due to climate change) for the months May–October based on various climate models. Historical data for the period 1984–2004 were used to test the system for the areas of Chania and Ilia.



from # All Medicine by Alexandros G. Sfakianakis via alkiviadis.1961 on Inoreader http://ift.tt/2tRo8Zk

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