70,082 research outputs found
Approximation of fuzzy numbers by convolution method
In this paper we consider how to use the convolution method to construct
approximations, which consist of fuzzy numbers sequences with good properties,
for a general fuzzy number. It shows that this convolution method can generate
differentiable approximations in finite steps for fuzzy numbers which have
finite non-differentiable points. In the previous work, this convolution method
only can be used to construct differentiable approximations for continuous
fuzzy numbers whose possible non-differentiable points are the two endpoints of
1-cut. The constructing of smoothers is a key step in the construction process
of approximations. It further points out that, if appropriately choose the
smoothers, then one can use the convolution method to provide approximations
which are differentiable, Lipschitz and preserve the core at the same time.Comment: Submitted to Fuzzy Sets and System at Sep 18 201
Fuzzy reasoning spiking neural P systems revisited: A formalization
Research interest within membrane computing is becoming increasingly interdisciplinary.In particular, one of the latest applications is fault diagnosis. The underlying mechanismwas conceived by bridging spiking neural P systems with fuzzy rule-based reasoning systems. Despite having a number of publications associated with it, this research line stilllacks a proper formalization of the foundations.National Natural Science Foundation of China No 61320106005National Natural Science Foundation of China No 6147232
Quantification of temporal fault trees based on fuzzy set theory
© Springer International Publishing Switzerland 2014. Fault tree analysis (FTA) has been modified in different ways to make it capable of performing quantitative and qualitative safety analysis with temporal gates, thereby overcoming its limitation in capturing sequential failure behaviour. However, for many systems, it is often very difficult to have exact failure rates of components due to increased complexity of systems, scarcity of necessary statistical data etc. To overcome this problem, this paper presents a methodology based on fuzzy set theory to quantify temporal fault trees. This makes the imprecision in available failure data more explicit and helps to obtain a range of most probable values for the top event probability
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