Dimension-reducing feature extraction neural network techniques which also preserve neighbourhood relationships in data have traditionally been the exclusive domain of Kohonen self organising maps. Recently, we introduced a novel dimension-reducing feature extraction process, which is also topographic, based upon a Radial Basis Function architecture. It has been observed that the gener-alisatio...

Neural network process modelling needs the use of experimental design and studies. A new neural network constructive algorithm is proposed. Moreover, the paper deals with the influence of the parameters of radial basis function neural networks and multilayer perceptrons network in process modelling. Particularly, it is shown that the neural modelling, depending on learning approach, cannot be a...

Solubility data of solid in aqueous and different organic solvents are very important physicochemical properties considered in the design of the industrial processes and the theoretical studies. In this study, experimental solubility data of 666 pharmaceutical compounds in water and 712 pharmaceutical compounds in organic solvents were collected from different sources. Three different artificia...

Neural networks with radial basis functions method are used to solve a class of initial boundary value of fractional partial differential equations with variable coefficients on a finite domain. It takes the case where a left-handed or right-handed fractional spatial derivative may be present in the partial differential equations. Convergence of this method will be discussed in the paper. A num...

In this article the neural network speciication language EpsiloNN is presented. From an abstract speciication that is independent of the target computer architecture, a simulation source program for a workstation or a parallel computer can be generated. Neurocomputers requiring xed-point data types and arithmetic are supported too. The language design is based on an uniied neural network model ...

During recent decades, recognizing letters was a considerable discussion for artificial intelligence researchers and recognize letters due to the variety of languages and different approaches have many challenges. The Artificial Neural Networks (ANNs) are framed based on particular application such as recognition pattern and data classification through learning process is configured. So, it is ...

This paper shows the latest results of the EvRBF algorithm applied to classification problems. EvRBF is an evolutionary algorithm intended to automatically design Radial Basis Functions Neural Networks (RBFNN), being its main advantage that establishes the whole set of parameters of the nets. Key–Words: Radial basis function neural networks, evolutionary algorithms, evolutionary operators,EvRBF...

In this paper we present an extensive comparison between several feedforward neural network types in the context of a clinical diagnostic task, namely the detection of coronary artery disease (CAD) using planar thallium-201 dipyridamole stress-redistribution scintigrams. We introduce results from well-known (e.g. multilayer perceptrons or MLPs, and radial basis function networks or RBFNs) as we...

Since its emergence from the early 1980s, the field of Human Computer Interaction has moved on and advanced in many significant ways. It has opened up a world in which communication between human and computer has become easier and richer. Among the different modes of interaction, Gestures provide the most natural and convenient way of communication. Hence gesture recognition has been extensivel...

this paper investigates the residual stress fields in the vicinity of weld bead in hsla-65 steel weldments using a neural network. this study consists of two cases: (i) the experimental analysis was carried out the measurements of residual stresses by xrd technique. many different specimens that were subjected to different conditions were studied. the values and distributions of residual stress...