Analysis of methods of evaluation of the accuracy of input data for air condition assessment

Authors

  • Регина Владимировна Криваковская Pukhov Institute for Modelling in Energy Engineering, National Academy of Sciences of Ukraine 15, General Naumov Str. Kiev, 03164, Ukraine

DOI:

https://doi.org/10.15587/1729-4061.2012.5611

Keywords:

data unreliability, artificial intelligence, Bayes network

Abstract

The article concerns the issues of reliability of input data for modeling of admixtures propagation in the air, and possible results of unreliable input data application at further optimization and control of the air quality. The main sources of unreliable data are given. There are objectives of the research in the sphere of input data limitation, review of approaches, decreasing its effect. The requirements to the methods of overcoming of input data limitation, as well as certain demands determined by Ukrainian realias, were formulated. The method based on the Bayes networks was suggested to assess the probabilistic properties of the modeling results unreliability during the application of unreliable input data. The article reveals the advantages of Bayes networks and the stages of their plotting. The structure of the network was suggested and its variables were described to assess the results of modeling. There is an approach to find out the values of conditional probabilities for the network

Author Biography

Регина Владимировна Криваковская, Pukhov Institute for Modelling in Energy Engineering, National Academy of Sciences of Ukraine 15, General Naumov Str. Kiev, 03164

PhD Student

Department of design automation of energetic units

References

  1. Артемчук, В.А. Информационно-аналитическая система эколого-энергетического мониторинга [Текст] / В.А. Артемчук, О.А. Грибан // Моделювання та інформаційні технології. – 2010. – Т. 1, спец. вип. С. 120-128
  2. Яцишин, А.В. Комп’ютерні засоби прогнозування техногенних навантажень на атмосферу [Текст] / А.В. Яцишин, О.О. Попов, В.О. Артемчук // Східно-Європейський журнал передових технологій - 2009. – Вип. 5/2 (41). – С. 33-36.
  3. Mallet. V. Ensemble-based air quality forecasts: A multimodel approach applied to ozone [Текст] / V. Mallet, B. Sportisse // J. Geophys. Res. - 2006 , 111, D18302, doi:10.1029/2005JD006675.
  4. Кожевникова, М.Ф. Идентификация источников загрязнения: вычислительные методы [Текст] / М.Ф. Кожевникова, В.В. Левенец, И.Л. Ролик // Вопросы атомной науки и техники. - 2011. - №6. Серия: Вакуум, чистые материалы, сверхпроводники (19), с. 149-156.
  5. Попов, О.О. Математичне та комп’ютерне моделювання техногенних навантажень на атмосферу міста від стаціонарних точкових джерел забруднення [Текст] : дис. ... канд. техн. наук : 01.05.02 / О. О. Попов – К., 2010. – 198 с.
  6. Рассел С., Норвиг П. Искусственный интеллект: современный подход [Текст] : пер. с англ. М: “Вильямс”, 2006 — 1408 с.
  7. Али Мансур Номан Мархуб. Экспертная система поддержки принятия решений в интеллектуальной системе экологического мониторинга атмосферного воздуха промышленного региона (на примере г.Новомосковска Тульской области) [Текст] / автореф. дис. ... канд. техн. Наук. 05.13.06, 03.02.08 / Али Мансур Номан Мархуб - М., 2011 — 18 с.
  8. Johnson S. Integrated Bayesian Network frameworks for modeling complex ecological issues [Текст] / PhD thesis / S. Johnson - 2009.
  9. He L. A probabilistic reasoning-based decision support system for selection of remediation technologies for petroleum-contaminated sites [Текст] / L. He., C.W. Chan, G.H. Huang, G.M. Zeng. // Expert Systems with Applications — 2006 — Вип. 30 — с. 783–795

Downloads

Published

2012-12-13

How to Cite

Криваковская, Р. В. (2012). Analysis of methods of evaluation of the accuracy of input data for air condition assessment. Eastern-European Journal of Enterprise Technologies, 6(10(60), 44–47. https://doi.org/10.15587/1729-4061.2012.5611

Issue

Vol. 6 No. 10(60) (2012): Ecology

Section

Ecology

License

Copyright (c) 2014 Регина Владимировна Криваковская

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.