… In this paper, we propose a new method to conduct the analysis of variance using fussy
logic models(FLANOVA). The FLM used is specially designed for the analysis. The model is …

… presents an integrated fuzzy regression– analysis of variance (ANOVA) … fuzzy regression
models. This is because there is no clear cut as to which of the recent fuzzy regression model is …

… problem, fuzzy set theory is widely used to model the … fuzzy set theory to extend the classical
mean–variance (MV) portfolio selection model into mean–variance–skewness (MVS) model …

… In this section we propose the corresponding fuzzy volatility models (FCV) and derive the …
variance of the fuzzy coefficient. First we give a lemma for the kurtosis of RC GARCH model. …

… to analyze such data, the aim of this paper is to introduce for the first time an intuitionistic
fuzzy … for a case where the data are intuitionistic fuzzy rather than real numbers. The proposed …

… The definition of the fuzzy variance FVar of a general fuzzy random variable is based on the
… Based on this concept, we have defined the fuzzy variance of X as the fuzzy set associated …

… Different from Huang’s approach, we used skewness of fuzzy … and analyze fuzzy mean-variance-skewness
models. … -variance-skewness model and mean-semivariance model, we …

… variance is applied to evaluate the performance of a medium precision FOG. Allan variance
is also employed to identify and model … results of Allan variance analysis cannot evaluate the …

… fuzzy randomness and fuzzy probabilistic collapse analysis are explained briefly. Then the
implementation of fuzzy sensitivity indices for the uncertainty model … frame is analyzed under …

… This credibilistic skewness was derived for the triangular fuzzy variable. In this paper, we
extended the fuzzy mean–variance model with credibilistic skewness for the trapezoidal fuzzy …