Automated data processing for evaluation the hydrophysical state of the Black Sea water areas
The article explores the issues of collecting, structuring and displaying oceanographic information from spatially distributed sources. The aim of the work was to develop services for an intelligent information system (IIS) designed to assess the hydrophysical state of the Black Sea waters by creati...
Збережено в:
| Видавець: | State Institution Scientific Hydrophysical Centre of the National Academy of Sciences of Ukraine |
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| Дата: | 2020 |
| Автори: | , , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
State Institution Scientific Hydrophysical Centre of the National Academy of Sciences of Ukraine
2020
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| Теми: | |
| Онлайн доступ: | https://oceanographic-journal.org.ua/index.php/journal/article/view/29 |
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Організація
Oceanographic Journal (Problems, methods and facilities for researches of the World Оcean)| Резюме: | The article explores the issues of collecting, structuring and displaying oceanographic information from spatially distributed sources. The aim of the work was to develop services for an intelligent information system (IIS) designed to assess the hydrophysical state of the Black Sea waters by creating a library of ontological descriptions of the processing and displaying information in the IIS software environment. Article describes approaches to the creation of an automated data processing system for the assessment of the hydrophysical state of the Black Sea using the method of recursive reduction. The information about the main functions of IIS for displaying structured data for illuminating the hydrophysical situation is presented. To solve such a problem, a set of cognitive services built on the basis of cognitive IT platforms to ensure the processes of automatic and automated collection of oceanographic data, their structuring and presentation to the user in an interactive form was applied for the first time. The results of the work can be used during the development of an analytical system for the automation of scientific and applied problems associated with the use of operational oceanographic data. |
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