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  5. Algorithm increase exactness of prognostication process origin extraordinary situations on basis regressive models

Algorithm increase exactness of prognostication process origin extraordinary situations on basis regressive models

H. Ivanets, M. Ivanets
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Description: Prevention origin extraordinary situations is a complex legal, socio-economic, political, organizationally technical and other measures, directed on adjusting natural and technogenic safety, leadthrough estimation risk levels, done early reacting, on the threat origin extraordinary situations on the basis information of monitoring, examination, researches and prognoses, in relation to the chapter possibilities with the purpose non-admission their outgrowing in extraordinary situations or softening of them possible consequences. An important aspect in relation to prevention and warning origin extraordinary situations is timely prog-nostication process their origin with the purpose minimization consequences from them. For prognostication process origin extraordinary situations the methods of regressive analysis are widely utilized in the state. The regressive model such process, as a rule, carries nonlinear character and appears as a sedate polynomial. At the estimation model parameters a least-squares method not always is provide constancy dispersion tailings for every supervision or group of supervisions. It results in that the parameters regressive model will not have minimum dispersion, that worsens exactness of prognosis. In the article the algorithm of prognostication process origin extraordinary situations is offered taking into account the errors of regressive model and clari-fication estimations its parameters on the basis the self-weighted least-squares method. The results experimental researches con-firm efficiency of application the self-weighted least-squares method for the increase exactness prognostication process origin of extraordinary situations at the use regressive models. Can be drawn on the got results for the ground of organizationally-technical measures in relation to providing readiness subdivisions and formings of civil defence, in particular Government service on the extraordinary situations of Ukraine, for the adequate reacting or warning of extraordinary situations and minimization their pos-sible consequences.

Keywords: extraordinary situation, regressive model, self-weighted least-squares method, exactness of prognosis


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 Ivanets, H.V. and Ivanets, M.H. (2019), “Alhorytm pidvyshchennia tochnosti prohnozuvannia protsesu vynyknennia nadzvychainykh sytuatsii na osnovi rehresiinykh modelei” [Algorithm increase exactness of prognostication process origin extraordinary situations on basis regressive models], Science and Technology of the Air Force of Ukraine, No. 1(34), pp. 117-122. https://doi.org/10.30748/nitps.2019.34.16.