Intelligent system for modelling climate variability
Aim. The study describes a prototype of an intelligent system for modelling climate variability based on a database of multi-year series and historical evidence. The presented intelligent system allows climate events to be simulated as follows: one phenomenon at one point; one phenomenon in space; m...
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| Format: | Article |
| Language: | Russian |
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Dagestan State Technical University
2020-08-01
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| Series: | Вестник Дагестанского государственного технического университета: Технические науки |
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| Online Access: | https://vestnik.dgtu.ru/jour/article/view/806 |
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| _version_ | 1849250263748050944 |
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| author | P. G. Asalkhanov N. V. Bendik Ya. M. Ivanyo |
| author_facet | P. G. Asalkhanov N. V. Bendik Ya. M. Ivanyo |
| author_sort | P. G. Asalkhanov |
| collection | DOAJ |
| description | Aim. The study describes a prototype of an intelligent system for modelling climate variability based on a database of multi-year series and historical evidence. The presented intelligent system allows climate events to be simulated as follows: one phenomenon at one point; one phenomenon in space; many phenomena at one point and many phenomena in space. Methods. The choice of research methods was determined by the properties of source information and its volume: a series of observations over a long period, sampling over a short period, historical and archival materials, etc. Results. The article describes the main functions of the presented intelligent system, which expand the possibility of assessing the variability of climate characteristics by combining quantitative and qualitative information in the form of historical and archival evidence. The main functions of the system include the generation of event flows; estimation of the event probability; physical reconstruction of data using geoinformation systems; determination of the period between two rare events; and management of agricultural production under risk conditions. Conclusion. The advantage of the proposed system consists in increasing information about extreme events and improving the management efficiency by means of reducing risks. |
| format | Article |
| id | doaj-art-e747c7a6ccad40148e297af2df126f18 |
| institution | Kabale University |
| issn | 2073-6185 2542-095X |
| language | Russian |
| publishDate | 2020-08-01 |
| publisher | Dagestan State Technical University |
| record_format | Article |
| series | Вестник Дагестанского государственного технического университета: Технические науки |
| spelling | doaj-art-e747c7a6ccad40148e297af2df126f182025-08-20T03:57:19ZrusDagestan State Technical UniversityВестник Дагестанского государственного технического университета: Технические науки2073-61852542-095X2020-08-01472303910.21822/2073-6185-2020-47-2-30-39577Intelligent system for modelling climate variabilityP. G. Asalkhanov0N. V. Bendik1Ya. M. Ivanyo2A.A. Ezhevsky Irkutsk State Agrarian UniversityA.A. Ezhevsky Irkutsk State Agrarian UniversityA.A. Ezhevsky Irkutsk State Agrarian UniversityAim. The study describes a prototype of an intelligent system for modelling climate variability based on a database of multi-year series and historical evidence. The presented intelligent system allows climate events to be simulated as follows: one phenomenon at one point; one phenomenon in space; many phenomena at one point and many phenomena in space. Methods. The choice of research methods was determined by the properties of source information and its volume: a series of observations over a long period, sampling over a short period, historical and archival materials, etc. Results. The article describes the main functions of the presented intelligent system, which expand the possibility of assessing the variability of climate characteristics by combining quantitative and qualitative information in the form of historical and archival evidence. The main functions of the system include the generation of event flows; estimation of the event probability; physical reconstruction of data using geoinformation systems; determination of the period between two rare events; and management of agricultural production under risk conditions. Conclusion. The advantage of the proposed system consists in increasing information about extreme events and improving the management efficiency by means of reducing risks.https://vestnik.dgtu.ru/jour/article/view/806intelligent systemdatabaseknowledgebaseclimate event |
| spellingShingle | P. G. Asalkhanov N. V. Bendik Ya. M. Ivanyo Intelligent system for modelling climate variability Вестник Дагестанского государственного технического университета: Технические науки intelligent system database knowledgebase climate event |
| title | Intelligent system for modelling climate variability |
| title_full | Intelligent system for modelling climate variability |
| title_fullStr | Intelligent system for modelling climate variability |
| title_full_unstemmed | Intelligent system for modelling climate variability |
| title_short | Intelligent system for modelling climate variability |
| title_sort | intelligent system for modelling climate variability |
| topic | intelligent system database knowledgebase climate event |
| url | https://vestnik.dgtu.ru/jour/article/view/806 |
| work_keys_str_mv | AT pgasalkhanov intelligentsystemformodellingclimatevariability AT nvbendik intelligentsystemformodellingclimatevariability AT yamivanyo intelligentsystemformodellingclimatevariability |