F_(10.7)指数是太阳活动的重要指标,准确预测F_(10.7)指数有助于预防和缓解太阳活动对无线电通信、导航和卫星通信等领域的影响.基于F_(10.7)射电流量的特性,在双向长短时记忆网络(Bidirectional Long Short-Term Memory Network,BiLSTM...F_(10.7)指数是太阳活动的重要指标,准确预测F_(10.7)指数有助于预防和缓解太阳活动对无线电通信、导航和卫星通信等领域的影响.基于F_(10.7)射电流量的特性,在双向长短时记忆网络(Bidirectional Long Short-Term Memory Network,BiLSTM)基础上融入注意力机制(Attention),提出了一种基于BiLSTM-Attention的F_(10.7)预报模型.在加拿大DRAO数据集上其平均绝对误差(MAE)为5.38,平均绝对百分比误差(MAPE)控制在5%以内,相关系数(R)高达0.987,与其他RNN模型相比拥有优越的预测性能.针对中国廊坊L&S望远镜观测的F_(10.7)数据集,提出了一种转换平均校准(Conversion Average Calibration,CAC)方法进行数据预处理,处理后的数据与DRAO数据集具有较高的相关性.基于该数据集对比分析了RNN系列模型的预报效果,实验结果表明,BiLSTM-Attention和BiLSTM两种模型在预测F_(10.7)指数方面具有较好的优势,表现出较好的预测性能和稳定性.展开更多
The solar 10.7 cm radio flux,F_(10.7),a measure of the solar radio flux per unit frequency at a wavelength of 10.7 cm,is a key and serviceable index for monitoring solar activities.The accurate prediction of F_(10.7) ...The solar 10.7 cm radio flux,F_(10.7),a measure of the solar radio flux per unit frequency at a wavelength of 10.7 cm,is a key and serviceable index for monitoring solar activities.The accurate prediction of F_(10.7) is of significant importance for short-term or long-term space weather forecasting.In this study,we apply Back Propagation(BP)neural network technique to forecast the daily F_(10.7)based on the trial data set of F_(10.7) from 1980 to 2001.Results show that this technique is better than the other prediction techniques for short-term forecasting,such as Support Vector Regression method.展开更多
基于224 MHz欧洲非相干散射甚高频雷达(European incoherent scatter very high frequency radar,EISCAT VHF radar)在2003—2014年间所观测的极区中层冬季回波(polar mesosphere winter echoes,PMWE)数据,分别从出现率、持续时间、高...基于224 MHz欧洲非相干散射甚高频雷达(European incoherent scatter very high frequency radar,EISCAT VHF radar)在2003—2014年间所观测的极区中层冬季回波(polar mesosphere winter echoes,PMWE)数据,分别从出现率、持续时间、高度分布、日变化、季节变化方面分析讨论了PMWE的平均时空特征,并对国际上PMWE与太阳和地磁活动的相关关系理论中存在的一些问题进行了讨论.结果表明:PMWE出现的几率非常低且持续时间普遍较短,其平均出现率为3.26%,每次出现的平均持续时间为67 min;高度分布范围主要在62~70 km,且在66~67 km高度范围内出现率最高;PMWE大多出现在白天,极少出现在夜晚,且11月份的出现率较高,12月份的出现率非常低.本文的研究为解释PMWE形成的物理机制提供了有价值的参考.展开更多
文摘F_(10.7)指数是太阳活动的重要指标,准确预测F_(10.7)指数有助于预防和缓解太阳活动对无线电通信、导航和卫星通信等领域的影响.基于F_(10.7)射电流量的特性,在双向长短时记忆网络(Bidirectional Long Short-Term Memory Network,BiLSTM)基础上融入注意力机制(Attention),提出了一种基于BiLSTM-Attention的F_(10.7)预报模型.在加拿大DRAO数据集上其平均绝对误差(MAE)为5.38,平均绝对百分比误差(MAPE)控制在5%以内,相关系数(R)高达0.987,与其他RNN模型相比拥有优越的预测性能.针对中国廊坊L&S望远镜观测的F_(10.7)数据集,提出了一种转换平均校准(Conversion Average Calibration,CAC)方法进行数据预处理,处理后的数据与DRAO数据集具有较高的相关性.基于该数据集对比分析了RNN系列模型的预报效果,实验结果表明,BiLSTM-Attention和BiLSTM两种模型在预测F_(10.7)指数方面具有较好的优势,表现出较好的预测性能和稳定性.
基金Supported by the National Natural Science Foundation of China(41231066)the Foundation for Ministry of Science and Technology of China(2011CB811404)+1 种基金the Specialized Research Fund for State Key Laboratories of the CASthe Scientific Research Staring Foundation for Nanjing University of Information Science and Technology(2013x030)
文摘The solar 10.7 cm radio flux,F_(10.7),a measure of the solar radio flux per unit frequency at a wavelength of 10.7 cm,is a key and serviceable index for monitoring solar activities.The accurate prediction of F_(10.7) is of significant importance for short-term or long-term space weather forecasting.In this study,we apply Back Propagation(BP)neural network technique to forecast the daily F_(10.7)based on the trial data set of F_(10.7) from 1980 to 2001.Results show that this technique is better than the other prediction techniques for short-term forecasting,such as Support Vector Regression method.
