We first present a brief review of the essential fuzzy system models: namely: (1) Zadeh’s rule base model, (2) Takagi and Sugeno’s model which is partly a rule base and partly a regression function and (3) TürkÅŸen’s fuzzy regression functions where a fuzzy regression function corresponds to each fuzzy rule. Next, we review the well known FCM algorithm which lets one to extract Type 1 membership values from a given data set for the development of Type 1 fuzzy system models as a foundation for the development of Full Type 2 fuzzy system models. For this purpose, we provide an algorithm which lets one to generate Full Type 2 membership value distributions for the development of second order fuzzy system models with our proposed second order data analysis. If required, then one can generate Full Type 3, ..., Full Type n fuzzy system models with an iterative execution of our algorithm. We present our application results graphically for TD_Stockprice data with respect to two validity indexes, namely: (1) Çelikyılmaz-TürkÅŸen and (2) Bezdek indexes.

fuzzy rule bases, fuzzy regression functions, Type 1, Full Type 2 fuzzy system models, stockprice data analysis.