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...
In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is com...
Abstract. The paper presents methods for model checking a class of possibly infinite state concurrent programs using various types of bi-simulation reductions. The proposed method...
The join of two sets of facts, E1 and E2, is defined as the set of all facts that are implied independently by both E1 and E2. Congruence closure is a widely used representation f...
This work presents a performance analysis of a Multi-Branches Genetic Programming (MBGP) approach applied in symbolic regression (e.g. function approximation) problems. Genetic Pro...