Бакалаврські роботи (ШІ)

Постійне посилання зібрання

https://ela.kpi.ua/handle/123456789/52507
У зібранні розміщено бакалаврські проекти (роботи) на здобуття ступеня бакалавра.

Переглянути

Перегляд Бакалаврські роботи (ШІ) за Автор "Baranovska, Lesia Veleriivna"

Зараз показуємо 1 - 1 з 1
  • Ескіз
    ДокументВідкритий доступ
    Artificial Intelligence System for Trends Analysis in Allergenic Hazard and Allergen Spread in Kyiv City
    (Igor Sikorsky Kyiv Polytechnic Institute, 2024) Brovko, Danil Vitaliiovych; Baranovska, Lesia Veleriivna
    Bachelor’s thesis: 57 p., 20 figures, 2 tables, 31 references, 3 appendixes. The subject of the research is pollinosis development in the human body. The object of the study is to model the allergenic hazard of ragweed pollen in each district of Kyiv depending on weather conditions. The purpose of the work is to create an artificial intelligence system called “PolliWeather” to track and predict the allergenic hazard and allergen spread of ragweed pollen depending on weather conditions and the districts of Kyiv. The idea behind it is to inform people about the level of allergenic hazard in different city districts. The relevance of the research. System analysis can be used to study phenomena from various fields of science. And one of the most important ones is medicine. Hundreds of millions of people suffer from pollinosis. This disease manifests as acute rhinitis, bronchitis, conjunctivitis, and sometimes even bronchial asthma. Thus, helping people to fight pollinosis is highly relevant. This research is a continuation of the paper “Mathematical Model of the Trend of Allergenic Hazard and Allergen Spread in Kyiv City”, presented by the author Brovko D. V. at the contest of the Junior Academy of Sciences of Ukraine in 2020. The article “Artificial Intelligence System for Trends Analysis in Allergenic Hazard and Allergen Spread in Kyiv City” by Brovko D. V. and Baranovska L. V. has been accepted for publication in the “International Scientific Technical Journal “Problems of Control and Informatics”. The results show analysis and prediction of pollinosis development risk depending on the time of the day, season, and districts of Kyiv. With this information, people will be able to take measures in advance to avoid health problems.