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So, a natural way to deal with the seemingly inconsistent information is to take this imprecision into account in the Bayesian approach – e.g., by using fuzzy techniques.
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Fuzzy image processing uses fuzzy techniques in the various stages of an image processing task.
Annoyance criteria are treated as non-linear functions that can be obtained by using fuzzy logic modelling techniques.
The parameters likelihood and severity related to the hazards in an aluminum plate manufacturing plant are weighted by using Fuzzy Analytic Hierarchy Process (FAHP), then the orders of priority of 23 various hazard groups are determined by using Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method.
When fuzzy systems are designed by using fuzzy clustering, each cluster corresponds to a fuzzy rule.
Enhancing contrast by using fuzzy clustering allows to define the contours of the lesion correctly.
Firstly, the cluster centers are set randomly and the initial clustering results are obtained by using fuzzy membership matrix.
With the contrast enhancement by using fuzzy clustering an output that adequately defines the contours of the lesions is obtained.
In order to develop fuzzy models, using fuzzy clustering techniques for parameter identification, the model structure given by equation (6) was used.
In 2007, Roy (2007) solved two-person multi-criteria bi-matrix games using fuzzy programming technique.
We find that by simultaneously combining the results of different detection techniques using fuzzy logic, better results can be obtained.
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