Intuitionistic fuzzy linear regression analysis
- 989 Downloads
Linear regression analysis in an intuitionistic fuzzy environment using intuitionistic fuzzy linear models with symmetric triangular intuitionistic fuzzy number (STriIFN) coefficients is introduced. The goal of this regression is to find the coefficients of a proposed model for all given input–output data sets. The coefficients of an intuitionistic fuzzy regression (IFR) model are found by solving a linear programming problem (LPP). The objective function of the LPP is to minimize the total fuzziness of the IFR model which is related to the width of IF coefficients. An illustrative example is also presented to depict the solution procedure of the IFR problem by using STriIFNs.
KeywordsLinear programming Decision analysis Uncertainty modelling Fuzzy sets Intuitionistic fuzzy regression analysis Symmetric triangular intuitionistic fuzzy numbers
Unable to display preview. Download preview PDF.
- Angelov, P. (1997). Optimization in an intuitionistic fuzzy environment. Fuzzy Sets and Systems, 68, 301–306.Google Scholar
- Mahapatra, B. S., & Mahapatra, G. S. (2010). Intuitionistic fuzzy fault tree analysis using intuitionistic fuzzy numbers. International Mathematical Forum, 5(21), 1015–1024.Google Scholar
- Mahapatra G. S., Roy T. K. (2009) Reliability evaluation using triangular intuitionistic fuzzy numbers arithmetic operations. International Journal of Mathematical and Statistical Sciences 1(1): 31–38Google Scholar
- Neter J., Wasserman W., Kutner M. H. (1985) Applied linear statistical models. Irwin, Homewood, ILGoogle Scholar
- Park, V., & Corson, S. (2001). Temporally-ordered routing algorithm (TORA), version 1, San Diego, CA: Flarion Technologies, Inc.Google Scholar