Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на этот ресурс:
http://hdl.handle.net/11701/29869
Полная запись метаданных
Поле DC | Значение | Язык |
---|---|---|
dc.contributor.author | Iakushev, Viktor Р. | - |
dc.contributor.author | Bure, Vladimir M. | - |
dc.contributor.author | Mitrofanova, Olga А. | - |
dc.contributor.author | Mitrofanov, Evgenii Р. | - |
dc.date.accessioned | 2021-07-14T13:53:05Z | - |
dc.date.available | 2021-07-14T13:53:05Z | - |
dc.date.issued | 2021-06 | - |
dc.identifier.citation | Iakushev V. Р., Bure V. M., Mitrofanova О. А., Mitrofanov Е. Р. Theoretical foundations of probabilistic and statistical forecasting of agrometeorological risks. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2021, vol. 17, iss. 2, pp. 174-182. | en_GB |
dc.identifier.other | https //doi.org/10.21638/11701/spbu10.2021.207 | - |
dc.identifier.uri | http://hdl.handle.net/11701/29869 | - |
dc.description.abstract | Еach model for forecasting agrometeorological risks based on the analysis of one-dimensional time series is effective for a certain range of initial information. In addition, the values of the initial observations can differ significantly for each specific case, respectively, the widespread use of one method for the analysis of arbitrary information can lead to significant inaccuracies. Thus, the problem of choosing a forecasting method for the initial set of agrometeorological data arises. In this regard, a universal adaptive probabilistic-statistical approach to predicting agrometeorological risks is proposed, which makes it possible to solve the problem of choosing a model. The article presents the results of the first stage of research carried out with the financial support of the Ministry of Education and Science of the Russian Federation a brief overview of the current state of research in this direction is presented, theoretical foundations for predicting agrometeorological risks for a possible onset of drought and frost have been developed, including the task of generating initial information, a description of basic forecasting models, and also a direct description of the proposed approach with a presentation of the general structure of an intelligent system, on the basis of which the corresponding algorithm can be developed and automated as directions for further work. | en_GB |
dc.description.sponsorship | This work is supported by the Russian Federation (agreement with the Ministry of Science and Education) (project N 075-15-2020-805 dated October 02, 2020). | en_GB |
dc.language.iso | ru | en_GB |
dc.publisher | St Petersburg State University | en_GB |
dc.relation.ispartofseries | Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 17; Issue 2 | - |
dc.subject | one-dimensional time series | en_GB |
dc.subject | forecasting | en_GB |
dc.subject | droughts | en_GB |
dc.subject | frosts | en_GB |
dc.subject | agrometeorological hazards | en_GB |
dc.subject | intelligent system | en_GB |
dc.title | Theoretical foundations of probabilistic and statistical forecasting of agrometeorological risks | en_GB |
dc.type | Article | en_GB |
Располагается в коллекциях: | Issue 2 |
Файлы этого ресурса:
Файл | Описание | Размер | Формат | |
---|---|---|---|---|
174-182.pdf | 422,96 kB | Adobe PDF | Просмотреть/Открыть |
Все ресурсы в архиве электронных ресурсов защищены авторским правом, все права сохранены.