Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems
This paper considers the problem of choosing the required set of characteristics for time series forecasting. The method of solving this problem on the basis of correlation matrix is proposed. A correlation matrix is constructed based on the prepared data, after which a list is formed for each varia...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2024-01-01
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| Series: | BIO Web of Conferences |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/64/bioconf_ForestryForum2024_04019.pdf |
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| author | Gusev Pavel Tavolzhanskij Alexander Zolnikov Vladimir Deniskina Antonina |
| author_facet | Gusev Pavel Tavolzhanskij Alexander Zolnikov Vladimir Deniskina Antonina |
| author_sort | Gusev Pavel |
| collection | DOAJ |
| description | This paper considers the problem of choosing the required set of characteristics for time series forecasting. The method of solving this problem on the basis of correlation matrix is proposed. A correlation matrix is constructed based on the prepared data, after which a list is formed for each variable, ordered by decreasing modulus of the correlation degree. Then linear regression models are trained and the quality of predictions for different sets of variables from the sorted list is compared. Next, a comparison is made for different values of sampling time to determine the optimal value for each variable. To apply the considered algorithm, information from various measuring sensors taking readings of climate variables in the forest lands was used. |
| format | Article |
| id | doaj-art-505f0e22a00b4e63b75c9fcd6ad7f778 |
| institution | Kabale University |
| issn | 2117-4458 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj-art-505f0e22a00b4e63b75c9fcd6ad7f7782024-12-06T09:33:14ZengEDP SciencesBIO Web of Conferences2117-44582024-01-011450401910.1051/bioconf/202414504019bioconf_ForestryForum2024_04019Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystemsGusev Pavel0Tavolzhanskij Alexander1Zolnikov Vladimir2Deniskina Antonina3Voronezh State Technical UniversityVoronezh State Technical UniversityVoronezh State University of Forestry and Technologies named after G.F. MorozovMoscow Aviation Institute (National Research University)This paper considers the problem of choosing the required set of characteristics for time series forecasting. The method of solving this problem on the basis of correlation matrix is proposed. A correlation matrix is constructed based on the prepared data, after which a list is formed for each variable, ordered by decreasing modulus of the correlation degree. Then linear regression models are trained and the quality of predictions for different sets of variables from the sorted list is compared. Next, a comparison is made for different values of sampling time to determine the optimal value for each variable. To apply the considered algorithm, information from various measuring sensors taking readings of climate variables in the forest lands was used.https://www.bio-conferences.org/articles/bioconf/pdf/2024/64/bioconf_ForestryForum2024_04019.pdf |
| spellingShingle | Gusev Pavel Tavolzhanskij Alexander Zolnikov Vladimir Deniskina Antonina Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems BIO Web of Conferences |
| title | Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems |
| title_full | Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems |
| title_fullStr | Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems |
| title_full_unstemmed | Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems |
| title_short | Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems |
| title_sort | analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2024/64/bioconf_ForestryForum2024_04019.pdf |
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