Paper Info
Title
An Interval Type-2 Fuzzy Regression Model With Crisp Inputs And Type-2 Fuzzy Outputs For Taiex Forecasting
Abstract
The type-2 fuzzy logic system permits us to model uncertainties existing in membership functions. Accordingly, this study aims to propose a linear framework for an interval type-2 fuzzy regression model based on the existing possibilistic models. In this model, vagueness is minimized, under the circumstances where the h-cut of observed value is included in predicted value. In this model both primary and secondary membership function of predicted value fit the observed value. This model, without the additional complexities, demonstrates its ability compared to previous type-2 fuzzy models. The Taiwan stock index forecasting is used to evaluate model efficiency.
Year
DOI
Venue
2016
10.1109/ICInfA.2016.7831906
2016 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA)
Keywords
Field
DocType
Interval type-2 fuzzy regression, Interval type-2 fuzzy number, Quadratic programming, Forecasting
Data mining,Fuzzy classification,Defuzzification,Fuzzy set operations,Fuzzy logic,Fuzzy set,Adaptive neuro fuzzy inference system,Fuzzy number,Membership function,Mathematics
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Narges Shafaei Bajestani1161.56
Ali Vahidian Kamyad211010.26
Assef Zare3161.90