The bias of the initial information flows intensities estimates of the global cyber-physical network

Authors

  • I. A. Zhukov
  • N. K. Pechurin
  • L. P. Kondratova

DOI:

https://doi.org/10.18372/2073-4751.64.15145

Keywords:

condition assessment, forecasting, cyber-physical networks, development of the Internet, initial information

Abstract

The use of the existing official statistical reporting for forecasting the development of the network, which provides deterministic estimates of input parameters, creates the danger of distorting the corresponding estimates of the initial information flows intensities generated by subscribers. The mapping (function of extreme balancing in the proposed estimation method) of the set of the input parameters values to the set of the estimates values is such that there is a bias in the estimates of the initial information flows intensities obtained by using the GDP indicator. In order to improve the accuracy of the Internet of Things development forecast in the context of the initial information flows dynamics, to taking into account the bias of estimates it is appropriate to move from the simple deterministic models of mathematical programming based on GDP and corresponding estimation methods to models and methods of stochastic programming.

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