Research from Sun Yat-sen University in the Area of Support Vector Machines Desc ribed (Evaluating the Geoeffectiveness of Interplanetary Coronal Mass Ejections: Insights from a Support Vector Machine Approach with SHAP Value Analysis)

Robotics & Machine Learning Daily News2024，Issue(Sep.11) ：79-80.

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Research from Sun Yat-sen University in the Area of Support Vector Machines Desc ribed (Evaluating the Geoeffectiveness of Interplanetary Coronal Mass Ejections: Insights from a Support Vector Machine Approach with SHAP Value Analysis)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on have been publish ed. According to news reporting from Zhuhai, People’s Republic of China, by News Rx journalists, research stated, “In this study, we compiled a data set of 510 interplanetary coronal mass ejections (ICME) events from 1996-2023 and trained a radial basis function support vector machine (RBF-SVM) model to investigate the geoeffectiveness of ICMEs and its dependence on the solar wind conditions observed at 1 au.”

Key words

Sun Yat-sen University/Zhuhai/People’s Republic of China/Asia/Emerging Technologies/Machine Learning/Support Vector Machines/Vector Machines

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出版年

2024

Robotics & Machine Learning Daily News

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