We develop a new decision making model based on the use of a unified approach between the probability, the weighted average and the ordered weighted averaging (OWA) operator in an uncertain environment that can be assessed with fuzzy numbers (FNs). We present a new aggregation operator called the fuzzy probabilistic ordered weighted averaging – weighted averaging (FPOWAWA) operator. We study it...

I n this paper, we review a new definition of fuzzy functional dependency based on conditional probability and i ts application to approximate data reduction related to operation of projection in classical relational database in order to construct fuzzy integrity constraints [l]. W e introduce the concept of partial fuzzy functional dependency which expresses the fact that a given attribute X d...

It is well accepted that in many real life situations information is not certain and precise but rather uncertain or imprecise. To describe uncertainty probability theory emerged in the 17th and 18th century. Bernoulli, Laplace and Pascal are considered to be the fathers of probability theory. Today probability can still be considered as the prevalent theory to describe uncertainty. However, in...

Fuzzy random variable is a combination of fuzzy variable and random variable, and can characterize both fuzziness and randomness in the real world. The mean chance of a fuzzy random event is an important concept in fuzzy random optimization, just like the probability of a stochastic event in stochastic optimization and the credibility of a fuzzy event in fuzzy optimization. In fuzzy random prog...

In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to...

In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stochastic linear programming problems, but also multiobjective fuzzy random linear programming problems through a probability maximization model. In a probability maximization model, it is necessary for the decision maker to specify permissible values of objective functions in advance, which have a great infl...

The previous methods to compute smooth molecular surface assumed that each atom in a molecule has a fixed position without thermal motion or uncertainty. In real world, the position of an atom in a molecule is fuzzy because of its uncertainty in protein structure determination and thermal energy of the atom. In this paper, we propose a method to compute smooth molecular surface for fuzzy atoms....

A fuzzy data fusion approach was used for human sperm morphology recognition analysis using 3-CCD camera image data. Fuzzy operators were used to create the relationship between abnormal sperm morphology and normal sperm aberrations after digitizing the images. The approaches have focused on frequencies of sperm with either abnormal morphology in semen analysis samples. In order to establish wh...

This paper proposes probabilistic default reasoning as a suitable approach to inheritance and recognition in uncertain and fuzzy object-oriented models. Firstly, we introduce an uncertain and fuzzy object-oriented model where a class property (i.e., an attribute or a method) can contain fuzzy sets interpreted as families of probability distributions, and uncertain class membership and property ...

Fuzzy measures are a generalization of probability measures for which additivity is removed and monotonicity is imposed instead. These measures have become a powerful tool in Decision Theory (see e.g. 12, the work of Schmeidler 21 and 3); moreover, the Choquet Expected Utility model generalizes the Expected Utility one, and this model offers a simple theoretical foundation for explaining phenom...