error measure criteria in SONFIS are Root Mean Square Error (RMSE), given as 

![0_image_0.png](0_image_0.png)

$$\mathrm{below:}\;R M S E=$$

where i t is output of SONFIS and *
i t is real answer; m is the number of test data 
(test objects). In the rest of paper, let m=19 and number of training data set =150. Figures 3 indicate the results of the aforesaid system. The indicated position in Figure 3a, b states minimum RMSE over the iterations. 

It is worth noting that upon this balancing criterion, we may lose the general dominant distribution on the data space. The performance of the obtained fuzzy rules on the test data has been portrayed in Figure 4(a). In employing of second algorithm (Figure3), we use- -for in this case- only exact rules i.e., one decision class in right hand of an if-then rule. Figure 6 depicts the performance of SORSTR over 7 random selection of SOM structure, respectively. The applied Error 

![0_image_1.png](0_image_1.png)

