An enhanced clustering function approximation technique for a radial basis function neural network

Fast Voltage and Power Flow Contingency Ranking Using Enhanced Radial Basis Function Neural Network

Deregulation of power system in recent years has changed static security assessment to the major concerns for which fast and accurate evaluation methodology is needed. Contingencies related to voltage violations and power line overloading have been responsible for power system collapse. This paper presents an enhanced radial basis function neural network (RBFNN) approach for on-line ranking of ...

A Novel Radial Basis Function Neural Network For Approximation

Two difficulties are involved with traditional RBF networks: the initial configuration of an RBF network needs to be determined by a trial-and-error method, and the performance suffers degradation when the desired locations of the center of the RBF are not suitable. A novel RBF network is proposed to overcome these difficulties. A new radial basis function is used for hidden nodes, and the numb...

A supervised radial basis function neural network

Performance Evaluation of a Radial Basis Function Neural Network Learning Algorithm for Function Approximation

This paper presents a performance analysis of the learning algorithm used to optimize radial basis function neural network in order to approach target functions from a set of input output pairs. This algorithm combines the growth criterion which adds neurons to the net until a stopping criteria is met for efficient design with a pruning strategy based on the relative contribution of each hidden...

Median radial basis function neural network

Radial basis functions (RBFs) consist of a two-layer neural network, where each hidden unit implements a kernel function. Each kernel is associated with an activation region from the input space and its output is fed to an output unit. In order to find the parameters of a neural network which embeds this structure we take into consideration two different statistical approaches. The first approa...