Possibility Theory-based Approach Research Articles

A Possibility Theory-Based Approach to the Ranking of Generalized Fuzzy Numbers

The ranking of fuzzy numbers plays a remarkable role in some application systems such as approximate reasoning, decision analysis, optimization and forecasting under fuzzy environments. In this paper, we propose a novel possibility degree formula of ranking generalized fuzzy numbers based on the possibility theory. The combined effects of the possibilistic mean and the variance/standard deviation on the ranking of generalized fuzzy numbers are considered. The axiomatic properties of the proposed ranking method are further verified. It is found that the possibilistic mean exhibits the dominant role as compared to the possibilistic variance or standard deviation. Some comparisons with the existing approaches are reported by carrying out lots of numerical examples. The observations reveal that the shortcomings in an existing method can be overcome. Generalized fuzzy numbers can be distinguished using a possibility degree. The developed ordering procedures of fuzzy numbers are consistent with human intuition, where the inherent uncertainty of fuzzy quantities is revealed.

Frequency scan analysis supported by a possibility theory-based approach

Fil: Romero Quete, Andres Arturo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - San Juan. Instituto de Energia Electrica. Universidad Nacional de San Juan. Facultad de Ingenieria. Instituto de Energia Electrica; Argentina

A dam assessment support system based on physical measurements, sensory evaluations and expert judgements

In engineering system control, human beings can play various key roles, in particular concerning measurement, global assessment and decision. This paper focuses on methods that allow the representation and aggregation of heterogeneous data (sensory evaluations, physical measurements, outputs of mathematical models, etc.) used in a global dam assessment process. It is acknowledged that in such complex systems many of the variables involved are evaluated with uncertainty. We propose a possibility theory-based approach to deal with all the different uncertain pieces of information and propagate them in aggregation models for global dam assessment. Finally, decision-making and communication applications relating to dam safety are presented.

Expression of Measurement Uncertainty in a Very Limited Knowledge Context: A Possibility Theory-Based Approach

At the application level, it is important to be able to define, around the measurement result, an interval which will contain an important part of the distribution of the measured values, that is, a confidence interval. This practice, which is acknowledged by the ISO Guide, is a major shift from the probabilistic representation as a confidence interval represents a set of possible values for a parameter associated with a confidence level. It can be considered as a probability-possibility transformation by viewing possibility distribution as encoding confidence intervals. In this paper, we extend previous works concerning the possibility expression of measurement uncertainty applied to situations where only very limited knowledge is available: one single measurement and unknown unimodal probability density

A possibility theory-based approach to the handling of uncertain relations between temporal points

Uncertain relations between temporal points are represented by means of possibility distributions over the three basic relations precedes, equals, and follows. Operations for computing inverse relation, for composing relations, for combining relations coming from different sources and pertaining to the same temporal points, or for representing negative information are defined. An illustrative example of representation and reasoning with uncertain temporal relations is provided. This article shows how possibilistic temporal uncertainty can be handled in the setting of point algebra. Moreover, the article emphasizes the advantages of the possibilistic approach over a probabilistic approach previously proposed. This work does for the temporal point algebra what the authors previously did for the temporal interval algebra. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 157–179, 2007.

An approximate reasoning based technique for oil assessment

In this paper we present a method based on the approximative reasoning and fuzzy set theory to the petroleum assessment. We introduce the ‘AFA System’ for Approximate Fuzzy Assessment System. In AFA system, we consider all available information which are usually imprecise and incomplete. We present a novel way to solve petroleum evaluation problem using a very efficient mechanism to deal with an incomplete and imprecise data. This mechanism is based on the fuzzy set theory and the possibility theory. We present a new deduction algorithm based on the fuzzy implications to find the total aggregation value of input parameters. In this example of use of the intelligent systems in petroleum engineering, fuzzy logic and approximate reasoning [Prade, H. (1987). Some issues in approximates and plausible reasoning in the FrameWork of a possibility theory-based approach (pp. 263–287), France] are used to better asses petroleum field in different regions. We show how our technique is efficient by comparing it to the traditional petroleum evaluation methods. We discuss the AFA system which is actually in use.