Using the hypothesis of λ-compactness in the process of forming training sample for forecasting neural network models

Authors

  • V. А. Krisilov
  • S. А. Yudin
  • D. M. Oleshko

Abstract

The problem of forming a qualitative training sample for neural networks in forecasting is solved. The possibility of use the hypothesis of λ-compactness at the step of forming an ensemble of recognizable classes is described. An advanced algorithm of forming a qualitative training sample is offered on the basis of the mechanisms considered.

Author Biographies

V. А. Krisilov

Krisilov V.А.

S. А. Yudin

Yudin S.А.

D. M. Oleshko

Oleshko D.M.

Issue

Section

Progressive information technologies, high-efficiency computer systems