This paper introduces a new approach based on chaotic strategy and neural network algorithm (NNA), called chaotic-based NNA (CNNA), to solve the optimal distributed generation allocation (ODGA), in radial distribution system (RDS). consists of determining locations sizes one or several generations (DGs) be inserted into RDS minimize multiple objectives while meeting set security limits. The rob...

An elliptical basis function (EBF) network is proposed in this study for the classification of remotely sensed images. Though similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. Since remotely sensed data often take on ...

The article is devoted to improving quality of decomposition of monotonic multi-component timeand frequency-domain signals. Decomposition filters operating with data sampled at geometrically spaced times or frequencies (at equally spaced times or frequencies on a logarithmic scale) are combined with artificial neural networks. A nonlinear processing unit, which can be considered as a deconvolut...

In this paper, to enhance voltage stability of distribution systems, a Network Topology based load flow results are used to calculate Voltage Stability Index (VSI). Then an algorithm for capacitor placement (CP) based on this voltage stability index is implemented to determine the optimal locations, number and size of fixed and/or switched shunt capacitors for voltage stability enhancement, in ...

This paper presents a new model of an artificial neural network solving classification problems – Local Transfer Function Classifier (LTF-C). Its structure is very similar to this of the Radial Basis Function neural network (RBF), however it utilizes entirely different learning algorithms, including not only changing positions and sizes of neuron reception fields, but also inserting and removin...

Optimization and characterization of porous materials have been extensively studied by various surface phenomena researchers. Efficient methods are required to predict the optimum values of operating parameters in different stages of material preparation and characterization processes. A novel method based on the application of a special class of radial basis function neural network known as Re...