Parameter estimation by anfis where dependent variable has outlier

Year 2014, Volume: 43 Issue: 2, 309 - 322, 01.04.2014

Türkan Erbay Dalkılıç , Kamile Sanlı Kula , Ayşen Apaydın

Abstract

Regression analysis is investigation the relation between dependent and
independent variables. And, the degree and functional shape of this relation is determinate by regression analysis. In case that dependent
variable has outlier, the robust regression methods are proposed to
make smaller the effect of the outlier on the parameter estimates. In
this study, an algorithm has been suggested to define the unknown
parameters of regression model, which is based on ANFIS (Adaptive
Network based Fuzzy Inference System). The proposed algorithm, expressed the relation between the dependent and independent variables
by more than one model and the estimated values are obtained by
connected this model via ANFIS. In the solving process, the proposed
method is not to be affected the outliers which are to exist in dependent
variable. So, to test the activity of the proposed algorithm, estimated
values obtained from this algorithm and some robust methods are compared. 

Keywords

Adaptive network, fuzzy inference, robust regression

References

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