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Заглавие документа: | Methodology for Solving High-dimensional Multi-Parameter Inverse Problems of Indirect Measurements |
Авторы: | Dolenko, Sergei Isaev, Igor Burikov, Sergei Dolenko, Tatiana Obornev, Eugeny Shimelevich, Mikhail |
Тема: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика |
Дата публикации: | 2023 |
Издатель: | Minsk : BSU |
Библиографическое описание источника: | Pattern Recognition and Information Processing (PRIP’2023). Artificial Universe: New Horisont : Proceedings of the 16 th International Conference, Belarus, Minsk, October 17–19, 2023 / Belarusian State University : eds. A. Nedzved, A. Belotserkovsky. – Minsk : BSU, 2023. – Pp. 162-165. |
Аннотация: | Inverse problems (IP) of indirect measurements are a class of IP encountered in most modern nature science experiments. Unfortunately, they are characterized by a number of properties making them hard to solve: they may be ill-posed or even incorrect, non-linear, and often they are characterized by high dimension by input and/or by output. As such, IP of indirect measurements require special methods to solve them. One of the classes of such methods are methods of machine learning (ML), which however possess special properties which should be taken into account when using them. In this paper, the authors suggest an outline of a special methodology, which can become the base for a standard scenario for processing data of indirect measurement IP with ML methods. The main notions underlying this methodology are also described and explained |
URI документа: | https://elib.bsu.by/handle/123456789/306223 |
ISBN: | 978-985-881-522-6 |
Финансовая поддержка: | This study has been performed at the expense of the grant of the Russian Science Foundation, project no. 19-11-00333, https://rscf.ru/en/project/19-11-00333/. |
Лицензия: | info:eu-repo/semantics/openAccess |
Располагается в коллекциях: | 2023. Pattern Recognition and Information Processing (PRIP’2023). Artificial Intelliverse: Expanding Horizons |
Полный текст документа:
Файл | Описание | Размер | Формат | |
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162-165.pdf | 180,34 kB | Adobe PDF | Открыть |
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