Matches in SemOpenAlex for { <https://semopenalex.org/work/W4306752162> ?p ?o ?g. }
Showing items 1 to 66 of
66
with 100 items per page.
- W4306752162 endingPage "435" @default.
- W4306752162 startingPage "426" @default.
- W4306752162 abstract "This paper presents different approaches for predicting the grade of geomagnetic Kp index using machine learning algorithms. The Kp index is considered to be an indicator of the energy input from the solar wind into the Earth’s magnetosphere. In this study, a wide range of machine learning algorithms were tested for the purpose of classifying Kp index grade, such as gradient boosting models, linear models, and neural networks. The main challenge of this classification task is a strong class imbalance, due to the fact that extreme values of Kp index are rarely observed. To overcome the issue, the SMOTE technique for minority classes oversampling was utilized. It is shown that SMOTE improves quality of the classification at far horizons. We also test time-series cross-validation for hyperparameters optimization and show that it does not improve the quality. All the models are scored against an out-of-sample test set to assess their quality and compare the results. Finally, we highlight the directions of further research based on the results obtained in this study." @default.
- W4306752162 created "2022-10-19" @default.
- W4306752162 creator A5048555877 @default.
- W4306752162 creator A5068588780 @default.
- W4306752162 creator A5072524356 @default.
- W4306752162 date "2022-10-19" @default.
- W4306752162 modified "2023-09-29" @default.
- W4306752162 title "Use of Classification Algorithms to Predict the Grade of Geomagnetic Disturbance" @default.
- W4306752162 cites W1678356000 @default.
- W4306752162 cites W2021890805 @default.
- W4306752162 cites W2064675550 @default.
- W4306752162 cites W2119892500 @default.
- W4306752162 cites W2148143831 @default.
- W4306752162 cites W2188361049 @default.
- W4306752162 cites W2911964244 @default.
- W4306752162 cites W2912734781 @default.
- W4306752162 cites W2964199361 @default.
- W4306752162 cites W3199524386 @default.
- W4306752162 doi "https://doi.org/10.1007/978-3-031-19032-2_44" @default.
- W4306752162 hasPublicationYear "2022" @default.
- W4306752162 type Work @default.
- W4306752162 citedByCount "0" @default.
- W4306752162 crossrefType "book-chapter" @default.
- W4306752162 hasAuthorship W4306752162A5048555877 @default.
- W4306752162 hasAuthorship W4306752162A5068588780 @default.
- W4306752162 hasAuthorship W4306752162A5072524356 @default.
- W4306752162 hasConcept C11413529 @default.
- W4306752162 hasConcept C119857082 @default.
- W4306752162 hasConcept C124101348 @default.
- W4306752162 hasConcept C154945302 @default.
- W4306752162 hasConcept C169903167 @default.
- W4306752162 hasConcept C197323446 @default.
- W4306752162 hasConcept C2776257435 @default.
- W4306752162 hasConcept C31258907 @default.
- W4306752162 hasConcept C41008148 @default.
- W4306752162 hasConcept C50644808 @default.
- W4306752162 hasConcept C8642999 @default.
- W4306752162 hasConceptScore W4306752162C11413529 @default.
- W4306752162 hasConceptScore W4306752162C119857082 @default.
- W4306752162 hasConceptScore W4306752162C124101348 @default.
- W4306752162 hasConceptScore W4306752162C154945302 @default.
- W4306752162 hasConceptScore W4306752162C169903167 @default.
- W4306752162 hasConceptScore W4306752162C197323446 @default.
- W4306752162 hasConceptScore W4306752162C2776257435 @default.
- W4306752162 hasConceptScore W4306752162C31258907 @default.
- W4306752162 hasConceptScore W4306752162C41008148 @default.
- W4306752162 hasConceptScore W4306752162C50644808 @default.
- W4306752162 hasConceptScore W4306752162C8642999 @default.
- W4306752162 hasLocation W43067521621 @default.
- W4306752162 hasOpenAccess W4306752162 @default.
- W4306752162 hasPrimaryLocation W43067521621 @default.
- W4306752162 hasRelatedWork W3100220443 @default.
- W4306752162 hasRelatedWork W4210794429 @default.
- W4306752162 hasRelatedWork W4212859008 @default.
- W4306752162 hasRelatedWork W4223456145 @default.
- W4306752162 hasRelatedWork W4280535922 @default.
- W4306752162 hasRelatedWork W4295309597 @default.
- W4306752162 hasRelatedWork W4309113015 @default.
- W4306752162 hasRelatedWork W4313854490 @default.
- W4306752162 hasRelatedWork W4322743207 @default.
- W4306752162 hasRelatedWork W4323894855 @default.
- W4306752162 isParatext "false" @default.
- W4306752162 isRetracted "false" @default.
- W4306752162 workType "book-chapter" @default.