Abstract
To this day, models such as empirical and dynamic, along with the multi-criteria analysis methods, have helped us towards the very understanding and estimation of all the functions (physical, chemical, biological) existing in freshwater ecosystems. The rich and variable system of the Greek lake Karla is a perfect candidate for our study and its purpose, which is to investigate the factors responsible for eutrophication (water temperature, nitrates, total phosphorus, secchi depth, chlorophyll-a) using fuzzy logic. In fuzzy logic, where the proposition can take any value in the close interval [0,1], there are infinite numbers of fuzzy implications which can be used; hence, a method of selecting the most appropriate implication is required. In this paper, we propose a method of evaluating fuzzy implications using available statistical data. The choice of the appropriate implication is based on the deviation of the true value of the fuzzy implication from the real values, as described by the statistical data.
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