... Reduction to Independent Variables: From. Normal Distribution to General Statistical Case to Fuzzy" (2001). Departmental Technical Reports (CS). 407. https ...

In many practical problems, we must combine ("fuse") data represented in different formats, e.g., statistical, fuzzy, etc. The simpler the data, ...

There are two general ways (not necessarily mutually exclusive) to develop a fuzzy regression model: (1) models where the relationship of the variables is fuzzy ...

Mar 16, 2022 · We will discuss what happens with “noise” – a random variable – when we apply some linear and nonlinear functions to it.

First, we assume our data is normal and set the so-called Gaussian membership functions. They are fuzzy versions of the classic Gaussian distribution, those ...

In this section, we propose some new methods of reduction for a type-2 fuzzy variable. Compared with the existing methods, the new methods are very much easier ...

In this paper, we develop a general fuzzy-statistical clustering approach for estimating change-points in different types of control charts with either fixed or ...

This book provides details on 22 probability distributions. Each distribution section provides a graphical visualization and formulas for distribution ...

The concepts of cumulative distribution function and empirical distribution function are investigated for fuzzy random variables.

In statistics, propagation of uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors)