## 5 Results and Evaluations
This indicator showed a lower value (0.0985) than the triangular MF. This type of MF also achieved better results for other indicators, where MSE shows a value of 0.0097, MAE 0.0957 and MAPE 48.05. Even the worst model with a trapezoidal function (model 1) showed better results in all monitored metrics than the best model with a triangular function. The penultimate form of the MF IT2 FL investigated is the Gaussian function. This form of function is very often used in stock market analysis see [38,39]. However, in this research, three-dimensional Gaussian functions showed the worst result. The best model in terms of Gaussian MFs was model 5 (LowerScale 0.8 LowerLag 0.2). It can be seen that, unlike the previous two types of MF, the Gaussian function showed the best results at the lowest level of uncertainty, while the other two types (triangular, trapezoidal) showed the best performance when including a large dose of uncertainty and uncertainty. The last investigated shape of the MF IT2 FL is the bell function. Based on the comparison with the previous mathematical functions, the bell function achieved excellent results with a very low level of uncertainty LowerScale 0.95 LowerLag 0.05, resp. LowerScale 0.9 LowerLag 0.1. However, in terms of quality and error rate, even the bell MF could not be compared much with the trapezoidal function. This type of fuzzy set with triangular fuzzy sets showed very close results. T2 FS are characterized by three-dimensional MF. The degree of membership for each element of a type-2 fuzzy set is a fuzzy set in [0,1]. The third dimension provides additional degrees of freedom to capture more information. Type-2 fuzzy sets are useful in circumstances where it is difficult to determine the exact membership function for fuzzy sets, which is useful for incorporating uncertainties. However, the use of type-2 \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model** & **RMSE** & **MSE** & **MAE** & **MAPE** \\ \hline Model (1) & 0.1754 & 0.0308 & 0.1621 & 91.47 \\ Model (2) & 0.1675 & 0.0280 & 0.1566 & 87.23 \\ Model (3) & 0.1674 & 0.0280 & 0.1568 & 87.18 \\ Model (4) & 0.1693 & 0.0287 & 0.1586 & 88.18 \\ Model (5) & 0.1716 & 0.0295 & 0.1607 & 89.46 \\ Model (6) & 0.1741 & 0.0303 & 0.1629 & 90.83 \\ Model (7) & 0.1767 & 0.0312 & 0.1651 & 92.23 \\ Model (8) & 0.1795 & 0.0333 & 0.1701 & 95.25 \\ Model (9) & 0.1825 & 0.0333 & 0.1701 & 95.25 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Evaluation the level of uncertainty for bell IT2 MF. fuzzy sets in practice has been limited due to the significant increase in computational complexity required to implement them. IT2 FS are characterized by secondary membership functions that have only values of 0 or 1. This limitation greatly simplifies the computational requirements associated with performing inferences with type-2 sets. Based on the evaluation and comparison of individual forms of mathematical functions of fuzzy logic according to selected indicators, it can be stated that the trapezoidal form of MF is best suited to the analysis of the stock market. This is followed by a triangular and bell shape, and the worst results were achieved by the widely used Gaussian shape MF. Another finding resulting from the evaluation is the fact that while the trapezoidal MF shows the best performance, this excellent performance was only achieved with a large dose of uncertainty or uncertainty included in the three-dimensional functions that IT2 FL uses. It is similar with triangular MF. On the contrary, although the bell and Gaussian functions performed worse, they did not need as much uncertainty for their best performance.