Various kinds of fuzzy regressionmodels are introduced in the literature andmany different methods are proposed to estimate fuzzy parameters of the models. In this study, a new approach is introduced to find the parameters of a linear fuzzy regression, with fuzzy outputs, the input data of which is measured by crisp numbers. Based on a non-equality possibility index, a new objective function is...

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 ...

Some recent advances in stability and optimality for the nonlinear receding horizon control (NRHC) or the nonlinear model predictive control (NMPC) are assessed. The NRHCs with terminal conditions are surveyed in terms of a terminal state equality constraint, a terminal cost, and a terminal constraint set. Other NRHCs without terminal conditions are surveyed in terms of a control Lyapunov funct...

In this paper we explore the possibility of introducing the equality symbol in the languages of Fuzzy Description Logics (FDLs) interpreted as a similarity relation. The goal is twofold: dealing with attribute-value representations at the domain objects level, and integrating the treatment of similarities inside the description languages and their corresponding knowledge bases. Source URL: http...

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Today, claims for social justice seem to divide into two types: claims for the redistribution of resources and claims for the recognition of cultural difference. Increasingly, these two kind of claims are polarized against one another. As a result, we are asked to choose between class politics and identity politics, social democracy and multiculturalism, redistribution and recognition. These, h...

Linear constraints occur naturally in many reasoning problems and the information that they represent is often uncertain. There is a difficulty in applying AI uncertainty formalisms to this situation, as their representation of the underlying logic, either as a mutually exclusive and exhaustive set of possibilities, or with a propositional or a predicate logic, is inappropriate (or at least unh...