This paper presents a novel technique which may be used to determine an appropriate threshold for interpreting the outputs of a trained Radial Basis Function (RBF) classifier. Results from two experiments demonstrate that this method can be used to improve the performance of RBF classifiers in practical applications.

As an internal parameter of ball milling process, grinding concentration (GC) is not able to be measured directly. According to ball mill’s principle, based on radial base function (RBF) network, a soft sensor method is presented to estimate the ball mill’s GC. And a novel grey relation analysis method as a way to determine the secondary variables is proposed. Simulation results demonstrate tha...

In this study, the radial distribution and gravimetric storage capacities of hydrogen on coronene (C24H12) and its Si substituted forms, C24H12, C24-nSinH12 (n= 4-24), have been investigated at 298 K and 0.1 MPa (standard situation) using (N,V,T) Monte Carlo simulation by Lennard-Jones (LJ) 12-6 potential. The results show that the increase of number of silicon substitution doesn’t have any eff...

In this paper we apply normalized radial basis function networks to function learning and in nonparametric classification. A simple parameter learning technique is proposed and convergence and the rates of convergence of the empirically trained networks are studied theoretically and in computer experiments.