in this article the researcher, comparing semivariance and calculated beta on basis of it to the variance and common beta, has tried to see whether downside beta criteria (semivariance and calculated beta on basis of it) have any preference over the common risk criteria (variance and common bata) or not. in order to achieve this, weekly data of 55 sample companies were gathered in a 6-year peri...

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.

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.

Let $ f: {\mathcal H} \rightarrow \mathbb{R} be a convex differentiable function whose solution set {{\rm{argmin}}}\; f is nonempty. To attain of the problem \min_{\mathcal H}f $, we consider second order dynamic system \;\ddot{x}(t) + \alpha \, \dot{x}(t) \beta (t) \nabla f(x(t)) c x(t) = 0 where positive such that \lim_{t\rightarrow +\infty}\beta(t) +\infty $. By imposing adequate hypothesis ...

In this paper we show how ideas from spline theory can be used to construct a local basis for the space of translates general iterated Brownian Bridge kernel $k_{\beta,\varepsilon}$ $\beta\in\mathbb{N}$, $\varepsilon\geq 0$. simple case $\beta=1$, derive an explicit formula corresponding Lagrange basis, which allows us solve interpolation problems without inverting any linear system. We use pro...

In this paper, a tree-based encoding method is introduced to represent the Beta basis function neural network. The proposed model called Flexible Beta Basis Function Neural Tree (FBBFNT) can be created and optimized based on the predefined Beta operator sets. A hybrid learning algorithm is used to evolving FBBFNT Model: the structure is developed using the Extended Genetic Programming (EGP) and...