Adaptive neural network is a powerful tool for prediction of air pollution abatement scenarios. But it is often difficult to avoid overfit during the training of adaptive neural n...
Controlling non-affine non-linear systems is a challenging problem in control theory. In this paper, we consider adaptive neural control of a completely non-affine pure-feedback s...
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
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) Net...
This paper outlines a radial basis function neural network approach to predict the failures in overhead distribution lines of power delivery systems. The RBF networks are trained ...
Grant Cochenour, Jerad Simon, Sanjoy Das, Anil Pah...