Technology of forecasting of situations for systems with genetic principles of work

Authors

  • Євген Віталійович Вавілов Odessa I.I.Mechnikov national university, Dvoryanskaya str., 2,Odessa, 65082, Ukraine

DOI:

https://doi.org/10.15587/2312-8372.2013.12953

Keywords:

forecasting, genetic algorithm, quality, alternative

Abstract

Forecasting in the management and the need for its improvement using modern tools, including neural networks using analytical methods, expert systems, the method of mathematical statistics, fuzzy logic and statistics of nonnumerical objects, has become very important due to the situational methodology widely spread in the last decades. The central idea is the proposition that any social body, the production or manufacturing process is an open system. It adapts to the diverse internal and external environment. In this case, the main causes of what is happening within such system are beyond it. Therefore, such concepts as adaptation and the environment are critical to the effective management. In turn, the adaptation itself can be of two main types: situational, when changing environmental conditions, and promising proactive adaptation, based on the detection and early consideration of changing trends in the environment. In this case, control is based mainly on the so-called early control - proactive management. On the basis of what is stated above, the article shows that, genetic algorithms can be used for the proactive management, as it is not contrary to main stages of the theory of forecasting. The article summarizes the essence of the stages. As a result, it was concluded that the phased forecast based on the use of modern means, as a basis can contain eight main stages of situational methodology of forecasting.

Author Biography

Євген Віталійович Вавілов, Odessa I.I.Mechnikov national university, Dvoryanskaya str., 2,Odessa, 65082

Graduate student

References

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Published

2013-03-29

How to Cite

Вавілов, Є. В. (2013). Technology of forecasting of situations for systems with genetic principles of work. Technology Audit and Production Reserves, 2(1(10), 22–24. https://doi.org/10.15587/2312-8372.2013.12953

Issue

Vol. 2 No. 1(10) (2013): Technology audit and production reserves

Section

Technology audit

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Copyright (c) 2016 Євген Віталійович Вавілов

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