USING SIMULATION TO ESTIMATE A FUZZY REGRESSION MODEL
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Abstract
The researcher faces a lot of problems when testing the accuracy of the model to estimate the parameters of the fuzzy regression model, and to remedy this problem, the prediction error was reduced by generating variables that follow a normal distribution using the most famous and common method, which is the (Box-Muller) method, which depends on the method of generating random variables that follow the standard uniform distribution U(0,1), and then these variables are converted into independent random variables that follow the standard normal distribution to estimate the parameters of the model and with the aim of reducing the prediction error between the expected and actual concentrations This indicates model accuracy and model blur that represents uncertainty in model predictions. The lower these values, the better the model performs in terms of accuracy and reliability.
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