In this paper we use radial basis functions to solve multivariable integral equations. We use collocation method for implementation. Numerical experiments show the accuracy of the method.

in this research, the spatial distribution of electrical conductivity and ph of springs, ghanats and the base flow concentration places on the streams of central and south-west and central parts of the hamedan-bahar plain were evaluated. using different geostatistical methods such as kriging, minimum curvature, inverse distance, natural neighbor, local polynomial and radial basis functions, 108...

This paper describes a method for surface reconstruction from sparse three-dimensional (3D) data that performs the reconstruction by building a sequence of surfaces approximating the data at increasing level of details (LOD). The method is simple, fast and suitable for a progressive 3D data/model representation, archiving, transmission. The surface reconstruction is obtained by a volumetric met...

The reconstruction of spectral function from correlation in Euclidean space is a challenging task. In this paper, we employ the Machine Learning techniques terms radial basis functions networks to reconstruct finite number data. To test our method, first generate one type data using mock by mixing several Breit-Wigner propagators. We found that compared with other traditional methods, TSVD, Tik...

We study the problem of selecting the best parameter values to use for a support vector machine (SVM) with RBF kernel. Our methods extend the well-known formulas for AIC and BIC, and we present two alternative approaches for calculating the necessary likelihood functions for these formulas. Our first approach is based on using the distances of support vectors from the separating hyperplane. Our...

This paper presents the MRBF network, a new algorithm adapted from the RBF network, to construct the classifiers for predicting phenotypic resistance on 6 protease inhibitors. The performance of the prediction was measured by 10-fold cross-validation. The results show that MRBF gives the lowest average mean square error (MSE) when compared with the traditional RBF network and multiple linear re...

Early diagnosis of Parkinson’s Disease (PD) is crucial for effective neuroprotection and early management. Recent neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with 123 I-Ioflupane (DaTSCAN) have shown to detect even early stages of the disease. In this paper, we use the Striatal Binding Ratio (SBR) values that are calculated from ...

We propose and analyze new fast feature weighting algorithms based on different types of feature ranking. Feature weighting may be much faster than feature selection because there is no need to find cut-threshold in the raking. Presented weighting schemes may be combined with several distance based classifiers like SVM, kNN or RBF network (and not only). Results shows that such method can be su...

We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function in the reproducing kernel Hilbert space of the Gaussian RBF kernel, in the situation where the number of examples tends to infinity, the bandwidth of the Gaussian kernel tends to 0, and the regularization parameter is h...