In this paper, a non-probabilistic method based on fuzzy logic is used to update finite element models (FEMs). Model updating techniques use the measured data to improve the accuracy of numerical models of structures. However, the measured data are contaminated with experimental noise and the models are inaccurate due to randomness in the parameters. This kind of aleatory uncertainty is irreduc...

A new market based approach for transmission expansion planning in deregulated environments is presented in this paper. In this approach, transmission-planning decisions are made based on the electric power market conditions. The main contribution of this research is 1) Introducing a new probabilistic tool for analyzing the electric market conditions, 2) Defining new criteria for ranking transm...

Wind power point forecasting is the primary method to deal with its uncertainty. However, in many applications, the probabilistic interval of wind power is more useful than traditional point forecasting. Methods to determine the probabilistic interval of wind power point forecasting value is very essential to power system operations. Based on the bootstrap method, this paper proposed a wavelet ...

Learning ontologies from large text corpora is a well understood task while evolving ontologies dynamically from user-input has rarely been adressed so far. Evolution of ontologies has to deal with vague or incomplete information. Accordingly, the formalism used for knowledge representation must be able to handle this kind of information. Classical logical approaches such as description logics ...

Fuzzy logic is a logical calculus which operates with many truth values (while classical logic works with the two values of true and false). Since fuzzy logic considers the truth of scientific statements like something softened, it is fruitfully applied to the study of biological phenomena, biology is indeed considered the field of complexity, uncertainty and vagueness. In this paper fuzzy logi...

Hydroinformatics combines topics of modelling and decision-making, both of which have attracted a great deal of attention outside hydroinformatics from the point of view of uncertainty. Epistemic uncertainties are due to the inevitably incomplete evidence about the dependability of a model or set of competing models. Inherent uncertainties are due to the varying information content inherent in ...

A new model on European options with uncertainty of both randomness and fuzziness in output is presented, by introducing fuzzy logic to the stochastic financial model. The randomness and fuzziness in the systems are evaluated by both probabilistic expectation and fuzzy expectation, taking account of seller s/buyer s subjective judgment. Prices of European call/put options with uncertainty are g...

This paper presents probability and possibility as two measures to model different types of uncertainty in continuous dynamical systems. We analyze and compare how probability and possibility distribution evolve in a dynamical system modeled by differential equations, where initial conditions and/or parameter may be uncertain. Moreover, we propose a new algorithm for the numerical resolution of...

This paper uses a constraint set approach to linear programming problems with equality constraints whose coefficients and/or right-hand side values could be uncertain. We consider three types of uncertainty: probabilistic, fuzzy/possibilistic, and interval. The constraint set generated by the linear constraints under uncertainty is illdefined and difficult to generate. Our approach computes an ...

For modeling real-world problems and constructing intelligent systems, integration of different methodologies and techniques has been the quest and focus of significant interdisciplinary research effort. The advantages of such a hybrid system are that the strengths of its partners are combined and complementary to each other’s weakness. In particular, object orientation provides a hierarchical ...