Situational and inductive modelling in problems of extrapolation forecasting based on monitoring data

Authors

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2016.4.04

Keywords:

extrapolation, inductive and situational models, modelling and forecasting based on monitoring data, real-time and term forecasts

Abstract

The approach to forecasting phenomena and processes with extrapolations using monitoring data and based on the idea of situational-inductive modelling is proposed. According to this approach, results of situational modelling within the samples time series, which are characterized by the monotony of trends or quasi stationary behaviour of variables of models at the appropriate time intervals, form the basis for the subsequent construction of inductive models. Inductive models are performed as models of "levels" which are based on the results of the situational modelling. Herewith, on the basis of situational models within intervals where situational models are considered adequate, the operational forecasting (in real time) is carried out, and on the basis of inductive models by means of which within the observed data the evolution of situational models is controlled, the term forecasting is carried out to establish situational models for future time periods.

Author Biography

Dmytro V. Stefanyshyn, The Institute of Telecommunications and Global Information Space of the NAS of Ukraine, Kyiv, Ukraine

Dmytro V. Stefanyshyn,

Doctor of Science (Eng.), Lead researcher of the Institute of Telecommunications and Global Information Space of the NAS of Ukraine, Kyiv, Ukraine.

Research areas: system analysis, analysis and assessment of risk, decision making under uncertainty and risk, reliability and safety of complicated systems, forecasting.

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Published

2016-12-15

Issue

Section

Progressive information technologies, high-efficiency computer systems