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In probability theory variation in the parameters is modeled using probability density functions and in possibility theory it is modeled using fuzzy membership functions.
The agents' behavior was modeled using fuzzy rules built by means of content analysis of newspapers and in-depth interviews with experts from the financial area.
There is vagueness in pairwise comparisons, and this vagueness has been modeled using fuzzy concepts.
In addition, driver location and speed were modeled using fuzzy numbers to account for the uncertainty of their locations.
This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables.
This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables.
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Mathematical and graphical models are presented using fuzzy set and fuzzy logic concepts.
In this paper, a novel UA risk assessment model has been developed using fuzzy set theories.
The first is a microprocessor using fuzzy logic.
Cluster formation using fuzzy logic.
When fuzzy systems are designed by using fuzzy clustering, each cluster corresponds to a fuzzy rule.
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modeled using v2f
modeled using probabilistic
modeled using Couette
modeled using finite
modeled using suitable
modeled using density
modeled using different
modeled using Gaussian
modeled using colored
modeled using i
modeled using differential
modeled using linear
modeled using nonlinear
modeled using multiple
modeled using shell
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