MODELING PRODUCTIVITY OF CRIMEAN PINE BY USING FUZZY LOGIC APPLICATIONS
This study was addressed to obtain a model of Crimean pine's productivity by using a fuzzy logic application and compare its result to the model obtained from the application of multiple regression analysis in the Dedegul mountain district of the Beysehir watershed in the Mediterranean region, Turkey. In the study, environmental variables (slope position, altitude and soil depth) which are significantly related to site index were taken attention for modeling the productivity. Even thought the regression coefficient of the obtained model by performing multiple regression analysis was relatively high with 72.6 %, the productivity model obtained by using fuzzy logic approach was much better with an explained variance of 85.79 %. The results show that fuzzy logic application seems to be more suitable approach compared to multiple regression analysis due to the fact that it can explain not only linear but also nonlinear relationships.
Keywords: Black pine, Fuzzy logic, Site index, Height growth, Environmental factors.
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