in the mathematical analysis, there are some theorems and definitions that established for both real and fuzzy numbers. in this study, we try to prove  bernoulli's inequality in fuzzy real numbers with some of its applications. also, we prove two other theorems in fuzzy real numbers which are proved before, for real numbers.

fuzzy measures are suitable in analyzing human subjective evaluation processes. several different strategies have been proposed for distance of fuzzy numbers. the distances introduced for fuzzy numbers can be categorized in two groups:1. the crisp distances which explain crisp values for the distance between two fuzzy numbers.2. the fuzzy distance which introduce a fuzzy distance for normal fuz...

Fuzzy measures have been widely used to determine the degrees of subjective importance of evaluation items. However, the leniency error may exist when most attributes are assigned unduly high ratings. Because respondents often assign similarly complimentary scores, errors of positive leniency make it difficult to differentiate the importance of decision attributes. To reduce positive leniency i...

in this paper we introduce the root of a fuzzy number, and we present aniterative method to nd it, numerically. we present an algorithm to generatea sequence that can be converged to n-th root of a fuzzy number.

This paper transforms fuzzy number into clear number using the centroid method, thus we can research the traditional linear regression model which is transformed from the fuzzy linear regression model. The model’s input and output are fuzzy numbers, and the regression coefficients are clear numbers. This paper considers the parameter estimation and impact analysis based on data deletion. Throug...

the present article investigates the application of high order tsk (takagi sugeno kang) fuzzy systems in modeling photo voltaic (pv) cell characteristics. a method has been introduced for training second order tsk fuzzy systems using anfis (artificial neural fuzzy inference system) training method. it is clear that higher order tsk fuzzy systems are more precise approximators while they cover n...

A new multiobjective selection procedure for Genetic Algorithms based on the paradigms of fuzzy logic is discussed and compared to the niched Pareto selection procedure. In the example presented here the fuzzy logic procedure optimized the parameters of a series of functions in a more efficient manner than the niched Pareto approach. The main advantage that the fuzzy logic approach has over the...