The National Weather Service (NWS) Mesocyclone Detection Algorithms (MDA) use empirical rules to process velocity data from the Weather Surveillance Radar 1988 Doppler (WSR-88D). In this study Support Vector Machines (SVM) are applied to mesocyclone detection. Comparison with other classification methods like neural networks and radial basis function networks show that SVM are more effective in...

As the support vector (SV) number of a support vector machine (SVM) determines the execution speed of the testing phase, there have been diverse methods to reduce it. Although iterative preimage addition (IPA), belonging to the ‘reduced set construction’, is reported to be able to reduce a large portion of the SV number of a standard SVM when the kernel is a radial basis function (RBF), the fac...

The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Networks for financial forecasting applications. The theory of the SVM algorithm is based on statistical learning theory. Training of SVMs leads to a quadratic programming (QP) problem. Preliminary computational results f...

In this work, a procedure for rule extraction from radial basis function (RBFN) networks is proposed. The algorithm is based on the use of a support vector machine (SVM) as a frontier pattern selector. By using geometric methods, centers of the RBF units are combined with support vectors in order to construct regions (ellipsoids or hyper-rectangles) in the input space, which are later translate...

Nowadays an increasing number of people own mobile phones with built-in camera, able to take pictures. Thus, having a fast and fully automatic algorithm of image retrieval is considered a promising way to identify plant leaves on a mobile device. Our solution proposes a Support Vector Machine that provides a multi-class probability estimation with radial basis function kernel based on two descr...

Many techniques have been developed for mitigating the effects of outliers on the results of SVM classification, including fuzzy-SVMs and weighted-SVMs. This paper examines the effect that outliers have on weighted-SVMs and standard SVMs on artificially generated data, using linear, radial basis function, and polynomial kernels. We find that SVMs are robust in the presence of noise – outliers c...

In standard equispaced finite difference (FD) formulas, symmetries can make the order of accuracy relatively high compared to the number of nodes in the FD stencil. With scattered nodes, such symmetries are no longer available. The generalization of compact FD formulas that we propose for scattered nodes and radial basis functions (RBFs) achieves the goal of still keeping the number of stencil ...

This paper proposes a numerical method to the two-dimensional hyperbolic equations with nonlocal integral conditions. The nonlocal integral equation is of major challenge in the frame work of the numerical solutions of PDEs. The method benefits from collocation radial basis function method, the generalized thin plate splines radial basis functions are used.Therefore, it does not require any str...

Several radial basis function based methods contain a free shape parameter which has  a crucial role in the accuracy of the methods. Performance evaluation of this parameter in different  functions with various data has always been a topic of study. In the present paper, we consider studying the methods which determine an optimal value for the shape parameter in interpolations of radial basis  ...