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In this paper we address the problem of how to measure information conveyed by an Atanassov's intuitionistic fuzzy set (A-IFS for short) and a related concept of knowledge that is explicitly context oriented and useful from the point of view of a specific purpose, notably related to decision making. We pay particular attention to the relationship between the positive and negative information and a...
In recommender systems, the task of automatically deriving user profiles, encoding the actual preferences of users, covers a fundamental role. In this paper, we propose a strategy for learning and updating user profiles by using fuzzy sets that reveal to be a valid tool to model the vague and imprecise nature of preferences as well as the items to be recommended. The proposed adaptation strategy resembles...
In the work we consider the situation with exact classes and fuzzy information of object features. The classification error is presented for the two-class Bayes classifier. The results are received for the full probabilistic information. The new upper bound of the probability of an error is precise twice as much as the bound based on the information energy of fuzzy events.
One of the most important features of fuzzy set theory is its potential for the modeling of natural language expressions. Most works done on this topic focus on some parts of natural language, mostly those that correspond to the so-called “evaluating linguistic expressions”. We build constraints for the mathematical substitutes of these expressions to mark characteristic limits on an ordered scale...
Wind energy is becoming one of the most important and promising areas of renewable energy. During the past few years, wind energy generation underwent strong improvements in several fields including power electronics, mechanics, wind dynamics, etc. However, there is a high need to develop more intelligent control mechanisms that can handle the various sources of uncertainties encountered in wind turbines...
This paper presents a methodology to find optimal solutions for linear programming problems on imprecise conditions. By using α-cuts, the cumulative membership function and the classic fuzzy linear programming model, a fuzzy joint parameters where its left hand side is defined by any kind of fuzzy set and its right hand side is defined by linear fuzzy sets, is solved and its crisp output is found...
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