Solar Proton Events Prediction Using Learning Vector Quantity Network

摘要：

In order to improve the prediction accuracy, learning vector quantity (LVQ) was applied to construct solar proton event prediction model. LVQ is new type of neutral network based on competitive learning rule, which takes a supervised learning model. The structure of LVQ is a two layers neutral network. The input unit is the predictors which are some active region parameters correlated to proton event. The output unit is the class label of proton occurrence or not. Test result shows that the prediction model has high forecast accuracy and the LVQ is an effectual prediction method.

关键词： active region predictor weight vector competitive learning

作者: Li Rong Sun Yuan Cui Yanmei

作者单位: The Institution of Information Beijing WuZi University Beijing, China Center for Space Science and Applied Research Chinese Academy of Sciences Beijing, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 761-763

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）