i n troduction: cancer is a major cause of mortality in the modern world, and one of the most important health problems in societies. during recent years, research on cancer as a system biology disease is focused on molecular differences between cancer cells and healthy cells. most of the proposed methods for classifying cancer using gene expression data act as black boxes and lack biological i...

The discretization of values plays a critical role in data mining and knowledge discovery. The representation of information through intervals is more concise and easier to understand at certain levels of knowledge than the representation by mean continuous values. In this paper, we propose a method for discretizing continuous attributes by means of a series of fuzzy sets, which constitutes a f...

Abstract— In this paper, a new extended method of multi criteria decision making based on fuzzy-Topsis theory is introduced. fuzzy mcdm algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. Using a new index leads to procedure for choosing fuzzy ideal and negative ideal solutions directly from the fuzzy data observed alternatives.in this...

The purpose of this paper is to evaluate the revenue efficiency in the fuzzy network data envelopment analysis‎. ‎Precision measurements in real-world data are not practically possible‎, ‎so assuming that data is crisp in solving problems is not a valid assumption‎. ‎One way to deal with imprecise data is fuzzy data‎. ‎In this paper‎, ‎linear ranking functions are used to transform the full fuz...

in this study, we introduce and study a concept of distributed fuzzymodeling. fuzzy modeling encountered so far is predominantly of a centralizednature by being focused on the use of a single data set. in contrast to this style ofmodeling, the proposed paradigm of distributed and collaborative modeling isconcerned with distributed models which are constructed in a highly collaborativefashion. i...

The paper focuses on two large application areas of the Fuzzy Set Theory in ecological research, namely data analysis (in particular fuzzy cluster analysis and fuzzy kriging) and ecological modelling. Environmental data or classes of ecological objects can be defined as fuzzy sets with not sharply defined boundaries, that reflects better the continuous character of nature. Fuzzy sets are used t...

It is common in real life to find fuzzy information that comes from subjective judgments or the imprecision in measured data. Fuzzy approaches have been used to extend database systems in storing and updating imprecise information (data) and in processing imprecise queries. Consider a fuzzy query: find name, grade of quite good students and just tall students where age > 15. This query includes...