Follow this and additional works at: http://engagedscholarship.csuohio.edu/enece_facpub Part of the Computer Engineering Commons Publisher's Statement NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Approximate Reasoning. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, a...

This research aims to determine the maximum or minimum value of a Fuzzy Support Vector Machine (FSVM) Algorithm using optimization function. SVM is considered as an effective method data classification, opposed FSVM, which less on large and complex because its sensitivity outliers noise. One techniques used overcome this inefficiency fuzzy logic with ability select right membership function, si...

Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature and here the study centres on the use of the Generalized Radial Basis Function Neural Networks (GRBFNNs). An interesting property of the GRBF is that it can continuously and smoot...

in this paper, a novel matched filter based on a new kernel function with cauchy distribution is introduced to improve the accuracy ofthe automatic retinal vessel detection compared with other available matched filter‑based methods, most notably, the methods builton gaussian distribution function. several experiments are conducted to pick the best values of the parameters for the new designedfi...

Given a fuzzy logic system, how can we determine the membership functions that will result in the best performance? If we constrain the membership functions to a speci ̄c shape (e.g., triangles or trapezoids) then each membership function can be parameterized by a few variables and the membership optimization problem can be reduced to a parameter optimization problem. The parameter optimization ...

In rare situations like fundamental physics we perform experiments without knowing what their results will be. In the majority of real-life measurement situations, we more or less know beforehand what kind of results we will get. Of course, this is not the precise knowledge of the type \the result will be between a ? and a + ", because in this case, we would not need any measurements at all. Th...