The performance of a Radial Basis Functions network (RBF) can be increased with the use of an ensemble of RBF networks because the RBF networks are successfully applied to solve classification problems and they can be trained by gradient descent algorithms. Reviewing the bibliography we can see that the performance of ensembles of Multilayer Feedforward (MF) networks can be improved by the use ...

This paper presents a new multiobjective evolutionary algorithm applied to a radial basis function (RBF) network design based on mult iobjective particle swarm optimization augmented with local search features. The algorithm is named the memetic multiobjective particle swarm optimization RBF network (MPSON) because it integrates the accuracy and structure of an RBF network. The proposed algorit...

In recent years some attempts have been done to relate the RBF with wavelets [1,2] in handling high dimensional multiscale problems. To the author’s knowledge, however, the orthonormal and bi-orthogonal RBF wavelets are still missing in the literature. By using the nonsingular general solution and singular fundamental solution of differential operator [3], recently the present author made some ...

Active queue control aims to improve the overall communication network throughput, while providing lower delay and small packet loss rate. The basic idea is to actively trigger packet dropping (or marking provided by explicit congestion notification (ECN)) before buffer overflow. In this paper, two artificial neural networks (ANN)-based control schemes are proposed for adaptive queue control in...

In this paper we propose the idea of building a new software reliability models using Radial Basis Function (RBF) network. The RBF network is easy to design and the network structure can be represented in a simple mathematical equation. Our goal is to build a generalized model that can be used for software predication [1]. The RBF network was trained with a set of data collected from the testin...

Learning in radial basis function (RBF) networks is the topic of this paper. Particularly we address the problem of intialisation the centers and scaling parameters in RBF networks utilizing classiication tree algorithms. This method was introduced by Kubat in 1998. Algorithms for the calculation of the centers and scaling parameters in an RBF network are presented and numerical results for the...

The retinoblastoma gene Rb is the prototype tumor suppressor and is conserved in Drosophila. We use the developing fly retina as a model system to investigate the role of Drosophila Rb (rbf) during differentiation. This report shows that mutation of rbf and rhinoceros (rno), which encodes a PHD domain protein, leads to a synergistic delay in photoreceptor cell differentiation in the developing ...