172 research outputs found

    Noninteractive fuzzy rule-based systems

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    In this paper, we have introduced a noninteractive model for fuzzy rule-based systems. A critical aspect of this noninteractive model is the introduction of a new set of rules with fewer parameters and without considering the interaction between the functionality of inputs. The new noninteractive model of the fuzzy rule-based system represents the output as a linear combination of the nonlinear function of individual inputs

    A behavioral foundation for fuzzy measures

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    In Savage [41] a ‘behavioral foundation’ was given for subjective probabilities, to be used in the maximization of expected utility. This paper analogously gives a behavioral foundation for fuzzy measures, to be used in the maximization of ‘Choquet-expected utility’. This opens the way to empirical verification or falsification of fuzzy measures, and frees them of their ‘ad hoc’ character

    Evaluation of risk from acts of terrorism :the adversary/defender model using belief and fuzzy sets.

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    OptimShare: A Unified Framework for Privacy Preserving Data Sharing -- Towards the Practical Utility of Data with Privacy

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    Tabular data sharing serves as a common method for data exchange. However, sharing sensitive information without adequate privacy protection can compromise individual privacy. Thus, ensuring privacy-preserving data sharing is crucial. Differential privacy (DP) is regarded as the gold standard in data privacy. Despite this, current DP methods tend to generate privacy-preserving tabular datasets that often suffer from limited practical utility due to heavy perturbation and disregard for the tables' utility dynamics. Besides, there has not been much research on selective attribute release, particularly in the context of controlled partially perturbed data sharing. This has significant implications for scenarios such as cross-agency data sharing in real-world situations. We introduce OptimShare: a utility-focused, multi-criteria solution designed to perturb input datasets selectively optimized for specific real-world applications. OptimShare combines the principles of differential privacy, fuzzy logic, and probability theory to establish an integrated tool for privacy-preserving data sharing. Empirical assessments confirm that OptimShare successfully strikes a balance between better data utility and robust privacy, effectively serving various real-world problem scenarios

    Decentralized adaptive fuzzy control of robot manipulators

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    Critical infrastructure systems of systems assessment methodology.

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    Unfolding-based Improvements on Fuzzy Logic Programs

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    AbstractUnfolding is a semantics-preserving program transformation technique that consists in the expansion of subexpressions of a program using their own definitions. In this paper we define two unfolding-based transformation rules that extend the classical definition of the unfolding rule (for pure logic programs) to a fuzzy logic setting. We use a fuzzy variant of Prolog where each program clause can be interpreted under a different (fuzzy) logic. We adapt the concept of a computation rule, a mapping that selects the subexpression of a goal involved in a computation step, and we prove the independence of the computation rule. We also define a basic transformation system and we demonstrate its strong correctness, that is, original and transformed programs compute the same fuzzy computed answers. Finally, we prove that our transformation rules always produce an improvement in the efficiency of the residual program, by reducing the length of successful Fuzzy SLD-derivations
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