A utilization of adaptive approximation library in environmental monitoring system

The solution of environmental monitoring problems is often limited to the use of proprietary software, which can adversely affect costs, flexibility, and data integration. The need for environmental monitoring system is especially acute in the field of public environmental monitoring, where teams of potential users unite researchers from different areas of science from biology and chemistry to sociology and economics. Simulation technology of environmental monitoring involves three main areas of activity: observations of impact factors and environmental conditions; assessment of the current state of the environment; forecasting the state of the natural environment and assessing the projected condition. Simulation technology of environmental monitoring includes approximation methods as estimation tools. To investigate the areas that are affected by the rocket stages conducted, this article suggests the creation of demonstration zones. Such zones are characterized by numerous sources and high level of pollutants penetrating into the ground. This paper describes the adaptive library of approximation algorithms to assess the concentration of unburned UDMH in ground to the extent that this concentration was verified in the study and in samples from specific sites from the fall regions of expendable stages of the rocket. Thus, the adaptive library makes it possible to obtain a preliminary estimate of the concentration of an environmentally hazardous substance, which can subsequently form the basis for possible regulatory actions. A problem of the environmental impacts of rocket fuel components is used to demonstrate the implementation of adaptive library. To analyze the concentration of unburned UDMH in ground, it is proposed to use the data of expedition's ground samples from different fall regions at different times and under different weather conditions. We further show how several results illustrate the usage of proposed adaptive library. © 2020 International Multidisciplinary Scientific Geoconference. All rights reserved.

Petrunina E.1 , Beloglazov A.1 , Beloglazova L. 2 , Nikolskij A.1 , Pecherskij D.3
International Multidisciplinary Scientific Geoconference
Номер выпуска
  • 1 Moscow State Humanitarian and Economics University, Russian Federation
  • 2 RUDN University, Russian Federation
  • 3 Moscow State University of Food Production, Russian Federation
Ключевые слова
Adaptive approximation library; Environmental monitoring; Multi-extreme functions; Simulation technology
Дата создания
Дата изменения
Постоянная ссылка

Другие записи