Laser fluorescent method for monitoring leaks from petrol pipes based on the neural network algorithm

Белов, М. Л.; Shteingart, Alexander; Матросова, О. А.; Городничев, В. А.

doi:10.7463/0114.0676410

Cited by 1 publication

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“…Оптимальное состояние остановки наблюдений удовлетворяет [13,14] . Если задается функция f(i) -выигрыш при остановке наблюдений в состоянии i, то цена удовлетворяет соотношению , а сама цена определяется итерациями:…”

Section: результаты исследования и обсужденияunclassified

Model of monitoring of oil soil pollution and its termination

Germanova

Евгеньевна²,

Magdeeva

et al. 2021

Vestn. Ross. univ. družby nar., Ser. Agron. životnovod.

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The assessment of impact of oil production economic activities on land pollution in Russia contributes to evolutionary management decision making. Oil industrial pollution affects negatively flora and fauna. Thus, its important to identify the level of its exposure and danger, the site of contamination. A system approach is needed. When studying the environment, its necessary to consider the presence of risk situations and stochastic irreversible changes. Its essential to identify the nature and type of soil contamination with petroleum products using high-tech tools, intellectual procedures. The work considers modeling of such situation, forecasting and identification of oil contaminants. The submodel of optimal termination of monitoring is also considered. Ending monitoring of environmental optimization will result in lower monitoring costs, since monitoring oilcontaminated environments is an expensive and complex technological mechanism, often requiring satellite data. The proposed algorithm for modeling and system analysis is based on situational modeling. Evolutionary modeling allows to adapt the procedure (methodology) of forecasting and assessment to environmental risk factors. It increases the accuracy (formalization and evidence) and completeness of conclusions, the efficiency of situation analysis, which affects manageability of risk both for the oil complex and for individual enterprise in the industry. The results of the research may be used for development of software tools, in particular expert and predictive systems. Situational models are needed when oil companies are solving multi-criteria and multifactor problems.

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Section: результаты исследования и обсужденияunclassified