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In Mediterranean extensively used areas, the analysis of landscape features and related public preferences is complex, as the landscape pattern is highly fuzzy and land cover classes are often mixed.
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However, as a Cloud service environment encompasses many uncertainties that may hinder users to make sound decisions, it is highly desirable to handle fuzzy information when choosing a suitable service in an uncertain environment.
An interactive fuzzy goal programming method, by combining interactive methods, goal programming, and fuzzy programming, is highly applied to solve multi-objective problems because of its capability in controlling the satisfaction level and the compromise degree among the objectives implicitly (Torabi and Hassini 2008).
The role played by fuzzy models is highly variable for different methods.
As the process to be controlled is highly non-linear the PI-type fuzzy controller that will be used generally is not able to control the system adequately.
As the process to be controlled is highly nonlinear the usual PI-type fuzzy controller is not able to control these systems adequately.
In this paper, a method is presented for optimizing the problem of correlated multiple responses where relationship among response and design variables is highly nonlinear by means of Neuro-Fuzzy and principal component analysis derived desirability function.
Likewise, we defined busy vertices and free vertices in interval valued intuitionistic (S,T fuzzy graphs and studied their images under an isomorphism, which are highly important in fuzzy social networks.
What remained was a case that was highly circumstantial, requiring the jury to meld a montage of fuzzy snapshots into a clear picture.
Thus we conclude that studies involving the use of such a Fuzzy Expert System in providing diagnostic and predictive medical opinions are highly promising for the future.
We used two fuzzy search algorithms, together with manual curation, to estimate the proportion of clusters which are highly similar.
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