Regression parameters prediction in data set with outliers using neural network

Authors : Tahereh RAZZAGHNİA

Pages : 1170-1184

Doi:10.15672/hujms.544496

View : 16 | Download : 5

Publication Date : 2019-08-08

Article Type : Research Paper

Abstract :Popular regression techniques often suffer at the presence of data outliers. The different methods have proposed to make smaller the effect of the outlier on the parameter estimates. In this study, an algorithm has been addressed based on Adaptive network based fuzzy inference system to define the unknown parameters of regression model where dependent variable has outlier. So, three numerical examples are solved to test the activity of the proposed algorithm in regression model estimation. Also, the obtained results from the different methods, such as linear programming insert ignore into journalissuearticles values(LP); and fuzzy weights with linear programming insert ignore into journalissuearticles values(FWLP); are compared together. The results show that the proposed method is not to be affected the outliers in the solving process.
Keywords : Fuzzy regression, Outlier, Linear programming, Fuzzy least squares, Adaptive neural networks