Information system for assessing the informativeness of an epidemic process features
The primary objective of this study is to assess the informativeness of various parameters influencing epidemic processes utilizing the Shannon and Kullback–Leibler methods. These methods were selected based on their foundation in the principles of information theory and their extensive application...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | Ukrainian |
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Igor Sikorsky Kyiv Polytechnic Institute
2023-12-01
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| Series: | Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï |
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| Online Access: | http://journal.iasa.kpi.ua/article/view/297411 |
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| author | Ксенія Базілевич Олена Кіріленко Юрій Парфенюк Сергій Яковлев Сергій Кривцов Євген Меняйлов Вікторія Кузнєцова Дмитро Чумаченко |
| author_facet | Ксенія Базілевич Олена Кіріленко Юрій Парфенюк Сергій Яковлев Сергій Кривцов Євген Меняйлов Вікторія Кузнєцова Дмитро Чумаченко |
| author_sort | Ксенія Базілевич |
| collection | DOAJ |
| description | The primary objective of this study is to assess the informativeness of various parameters influencing epidemic processes utilizing the Shannon and Kullback–Leibler methods. These methods were selected based on their foundation in the principles of information theory and their extensive application in machine learning, statistics, and other relevant domains. A comparative analysis was performed between the results acquired from both methods, and an information system was designed to facilitate the uploading of data samples and the calculation of factor informativeness impacting the epidemic processes. The findings revealed that certain features, such as “Chronic lung disease,” “Chronic kidney disease,” and “Weakened immunity,” did not carry significant information for further analysis and hindered the forecasting process, as per the data set examined. The developed information system efficiently supports the assessment of feature informativeness, thereby aiding in the comprehensive analysis of epidemic processes and enabling the visualization of the results. This study contributes to the current body of knowledge by providing specific examples of applying the described algorithmic models, comparing various methods and their outcomes, and developing a supportive tool for analyzing epidemic processes. |
| format | Article |
| id | doaj-art-9da6a69f8d1e4de294d2e7a4213b998b |
| institution | Kabale University |
| issn | 1681-6048 2308-8893 |
| language | Ukrainian |
| publishDate | 2023-12-01 |
| publisher | Igor Sikorsky Kyiv Polytechnic Institute |
| record_format | Article |
| series | Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï |
| spelling | doaj-art-9da6a69f8d1e4de294d2e7a4213b998b2024-12-20T12:28:57ZukrIgor Sikorsky Kyiv Polytechnic InstituteSistemnì Doslìdženâ ta Informacìjnì Tehnologìï1681-60482308-88932023-12-01410011210.20535/SRIT.2308-8893.2023.4.08335752Information system for assessing the informativeness of an epidemic process featuresКсенія Базілевич0https://orcid.org/0000-0001-5332-9545Олена Кіріленко1https://orcid.org/0009-0005-8917-0878Юрій Парфенюк2https://orcid.org/0000-0001-5357-1868Сергій Яковлев3https://orcid.org/0000-0003-1707-843XСергій Кривцов4https://orcid.org/0000-0001-5214-0927Євген Меняйлов5https://orcid.org/0000-0002-9440-8378Вікторія Кузнєцова6https://orcid.org/0000-0003-3882-1333Дмитро Чумаченко7https://orcid.org/0000-0003-2623-3294National Aerospace University “Kharkiv Aviation Institute”, KharkivNational Aerospace University “Kharkiv Aviation Institute”, KharkivV. N. Karazin Kharkiv National University, KharkivNational Aerospace University “Kharkiv Aviation Institute”, KharkivNational Aerospace University “Kharkiv Aviation Institute”, KharkivV. N. Karazin Kharkiv National University, KharkivV. N. Karazin Kharkiv National University, KharkivNational Aerospace University “Kharkiv Aviation Institute”, KharkivThe primary objective of this study is to assess the informativeness of various parameters influencing epidemic processes utilizing the Shannon and Kullback–Leibler methods. These methods were selected based on their foundation in the principles of information theory and their extensive application in machine learning, statistics, and other relevant domains. A comparative analysis was performed between the results acquired from both methods, and an information system was designed to facilitate the uploading of data samples and the calculation of factor informativeness impacting the epidemic processes. The findings revealed that certain features, such as “Chronic lung disease,” “Chronic kidney disease,” and “Weakened immunity,” did not carry significant information for further analysis and hindered the forecasting process, as per the data set examined. The developed information system efficiently supports the assessment of feature informativeness, thereby aiding in the comprehensive analysis of epidemic processes and enabling the visualization of the results. This study contributes to the current body of knowledge by providing specific examples of applying the described algorithmic models, comparing various methods and their outcomes, and developing a supportive tool for analyzing epidemic processes.http://journal.iasa.kpi.ua/article/view/297411information systemepidemic processinformativeness of featuresshannon methodkullback–leibler method |
| spellingShingle | Ксенія Базілевич Олена Кіріленко Юрій Парфенюк Сергій Яковлев Сергій Кривцов Євген Меняйлов Вікторія Кузнєцова Дмитро Чумаченко Information system for assessing the informativeness of an epidemic process features Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï information system epidemic process informativeness of features shannon method kullback–leibler method |
| title | Information system for assessing the informativeness of an epidemic process features |
| title_full | Information system for assessing the informativeness of an epidemic process features |
| title_fullStr | Information system for assessing the informativeness of an epidemic process features |
| title_full_unstemmed | Information system for assessing the informativeness of an epidemic process features |
| title_short | Information system for assessing the informativeness of an epidemic process features |
| title_sort | information system for assessing the informativeness of an epidemic process features |
| topic | information system epidemic process informativeness of features shannon method kullback–leibler method |
| url | http://journal.iasa.kpi.ua/article/view/297411 |
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