Single value simulation of fuzzy variables
Fuzzy Sets and Systems
Multiobjective fuzzy linear regression analysis for fuzzy input-output data
Fuzzy Sets and Systems
Multi-objective fuzzy regression: a general framework
Computers and Operations Research - Special issue on artificial intelligence and decision support with multiple criteria
Outliers detection and confidence interval modification in fuzzy regression
Fuzzy Sets and Systems
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
An "orderwise" polynomial regression procedure for fuzzy data
Fuzzy Sets and Systems
Robust fuzzy regression analysis
Information Sciences: an International Journal
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The paper proposes three fuzzy regression models - concerning temperature and electricity load - based on real data. In the first two models the monthly temperature in a period of four years in a Polish city is analyzed. We assume the temperature to be fuzzy and its dependence on time and on the temperature in the previous month is determined. In the construction of the fuzzy regression models the least square methods was used. In the third model we analyze the dependence of the daily electricity load (assumed to be a fuzzy number) on the (crisp) temperature. Outliers, i.e. non-typical instances in the observations are identified, using a modification of an identification method known from the literature. The proposed method turns out to identify the outliers consistently with the real meaning of the experimental data.