Frost Forecasting considering Geographical Characteristics
Regional accuracy was examined using extreme gradient boosting (XGBoost) to improve frost prediction accuracy, and accuracy differences by region were found. When the points were divided into two groups with weather variables, Group 1 had a coastal climate with a high minimum temperature, humidity,...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2022/1127628 |
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| _version_ | 1832562078502617088 |
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| author | Hyojeoung Kim Jong-Min Kim Sahm Kim |
| author_facet | Hyojeoung Kim Jong-Min Kim Sahm Kim |
| author_sort | Hyojeoung Kim |
| collection | DOAJ |
| description | Regional accuracy was examined using extreme gradient boosting (XGBoost) to improve frost prediction accuracy, and accuracy differences by region were found. When the points were divided into two groups with weather variables, Group 1 had a coastal climate with a high minimum temperature, humidity, and wind speed and Group 2 exhibited relatively inland climate characteristics. We calculated the accuracy in the two groups and found that the precision and recall scores in coastal areas (Group 1) were significantly lower than those in the inland areas (Group 2). Geographic elements (distance from the nearest coast and height) were added as variables to improve accuracy. In addition, considering the continuity of frost occurrence, the method of reflecting the frost occurrence of the previous day as a variable and the synthetic minority oversampling technique (SMOTE) pretreatment were used to increase the learning ability. |
| format | Article |
| id | doaj-art-c881d630a89c4fea86686897ad5f86a8 |
| institution | Kabale University |
| issn | 1687-9317 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-c881d630a89c4fea86686897ad5f86a82025-02-03T01:23:34ZengWileyAdvances in Meteorology1687-93172022-01-01202210.1155/2022/1127628Frost Forecasting considering Geographical CharacteristicsHyojeoung Kim0Jong-Min Kim1Sahm Kim2Department of Applied StatisticsDivision of Science and MathematicsDepartment of Applied StatisticsRegional accuracy was examined using extreme gradient boosting (XGBoost) to improve frost prediction accuracy, and accuracy differences by region were found. When the points were divided into two groups with weather variables, Group 1 had a coastal climate with a high minimum temperature, humidity, and wind speed and Group 2 exhibited relatively inland climate characteristics. We calculated the accuracy in the two groups and found that the precision and recall scores in coastal areas (Group 1) were significantly lower than those in the inland areas (Group 2). Geographic elements (distance from the nearest coast and height) were added as variables to improve accuracy. In addition, considering the continuity of frost occurrence, the method of reflecting the frost occurrence of the previous day as a variable and the synthetic minority oversampling technique (SMOTE) pretreatment were used to increase the learning ability.http://dx.doi.org/10.1155/2022/1127628 |
| spellingShingle | Hyojeoung Kim Jong-Min Kim Sahm Kim Frost Forecasting considering Geographical Characteristics Advances in Meteorology |
| title | Frost Forecasting considering Geographical Characteristics |
| title_full | Frost Forecasting considering Geographical Characteristics |
| title_fullStr | Frost Forecasting considering Geographical Characteristics |
| title_full_unstemmed | Frost Forecasting considering Geographical Characteristics |
| title_short | Frost Forecasting considering Geographical Characteristics |
| title_sort | frost forecasting considering geographical characteristics |
| url | http://dx.doi.org/10.1155/2022/1127628 |
| work_keys_str_mv | AT hyojeoungkim frostforecastingconsideringgeographicalcharacteristics AT jongminkim frostforecastingconsideringgeographicalcharacteristics AT sahmkim frostforecastingconsideringgeographicalcharacteristics |