Detecting outliers in fuzzy regression analysis with asymmetric trapezoidal fuzzy data

A. Maleki; E. Pasha; Gh. Yari; T. Razzaghnia

doi:10.1117/12.923177

13 January 2012 Detecting outliers in fuzzy regression analysis with asymmetric trapezoidal fuzzy data

A. Maleki, E. Pasha, Gh. Yari, T. Razzaghnia

Proceedings Volume 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis; 834922 (2012) https://doi.org/10.1117/12.923177
Event: Fourth International Conference on Machine Vision (ICMV 11), 2011, Singapore, Singapore

Abstract

The existence of outliers in a set of experimental data can cause incorrect interpretation of the fuzzy linear regression results. This paper is to introduce some limitation on constraints of fuzzy linear regression models for determining fuzzy parameters with outliers by value trapezoidal fuzzy data.

Citation Download Citation

A. Maleki, E. Pasha, Gh. Yari, and T. Razzaghnia "Detecting outliers in fuzzy regression analysis with asymmetric trapezoidal fuzzy data", Proc. SPIE 8349, Fourth International Conference on Machine Vision (ICMV 2011): Machine Vision, Image Processing, and Pattern Analysis, 834922 (13 January 2012); https://doi.org/10.1117/12.923177

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