In this paper, we address the server selection problem for streaming applications on the Internet. The architecture we consider is similar to the content distribution networks con...
Scatterograms of the images of training set vectors in the hidden space help to evaluate the quality of neural network mappings and understand internal representations created by t...
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
Abstract. In this paper, we consider the problem of generating optimized, executable control code from high-level, symbolic specifications. In particular, we construct symbolic co...
This study develops a novel model, GA-SVR, for parameters optimization in support vector regression and implements this new model in a problem forecasting maximum electrical daily...