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Application of Bayesian networks for accuracy estimation of modeling results of the air pollution dispersion given inaccurate input data

Authors: Kryvakovska, Regina V.;

Application of Bayesian networks for accuracy estimation of modeling results of the air pollution dispersion given inaccurate input data

Abstract

The article deals with estimating the results accuracy of the modeling of air pollution dispersion when introducing inaccurate input data. Restrictions on accuracy estimation methods for Ukraine are considered. It is suggested to use Bayesian networks with discrete input variables to obtain the estimates. The structure of the network is presented, and the methods of filling the probability tables are proposed.

Розглянуто питання оцінювання точності результатів моделювання поширення домішок у повітрі в разі подання на вхід моделей неточних вхідних даних. Наведено обмеження на методи оцінювання точності для України. Для отримання оцінок запропоновано використання байєсових мереж з дискретними вхідними змінними. Подано структуру мережі та запропоновано методи заповнення таблиць імовірностей.

Рассмотрен вопрос оценки точности результатов моделирования распространения примесей в воздухе при подаче на вход моделей неточных входных данных. Приведены ограничения на методы оценки точности для Украины. Для получения оценок предложено использование байесовских сетей с дискретными входными переменными. Подана структура сети и предложены методы заполнения таблиц вероятностей.

Keywords

оцінювання стану атмосферного повітря; байєсові мережі довіри, atmospheric air assessment; Bayesian networks, оценка состояния атмосферного воздуха; байесовы сети доверия

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold