首页|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)
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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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.”
Sun Yat-sen UniversityZhuhaiPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupport Vector MachinesVector Machines
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