基于长短期记忆网络时序数据趋势预测及应用

为了研究状态监测大数据对设备运行状态的估计和预测,提出了一种人工经验与主成分分析相结合的长短期记忆网络方法（AEPCA-LSTM）,利用运行过程中的监测时序数据对设备运行趋势进行预测。首先,通过基于人工经验的主要成分分析方法（AEPCA）从状态监测系统中提取与目标变量最相关的状态变量作为输入;其次,利用长短期记忆网络（LSTM）对目标变量趋势变化进行预测,并考虑运行过程中新数据样本的持续产生,对模型进行定期更新,以提高模型的动态适应性。最后,将所提出的方法应用于船舶副机系统的涡轮增压器转速预测中,结果表明该方法相对于传统的PCA-LSTM和LSTM,具有更小的预测平均误差0.18037,即展现了其在时序数据趋势预测的优势。     

电磁屏蔽材料的研究进展

阐述了研究电磁屏蔽材料的重要性。综述了表层导电型、填充复合型、本征型导电高分子、导电织物、透明导电薄膜等电磁屏蔽材料的性能及特点,简要阐述了电磁屏蔽材料的发展趋势。     

Investigation of the planar midlatitude ionospheric trend under different levels of solar activity

A better understanding of the ionosphere through accurate mathematical models is no doubt a crucial element. This study focuses on the challenging problem of building a model representing the complex structure of the midlatitude ionosphere. Previous studies have shown that a regional planar model is suitable in representing the total electron content (TEC) trend in the midlatitude ionosphere in both hemispheres. In this study, the planar trend model for 12 non-overlapping northern hemisphere regions in three groups of geographically near 4 regions is further investigated under different levels of solar activity; low, moderate and high. To that end, the coefficients of the model are estimated in the least squares sense using total electron content values from global ionospheric maps (GIMs) for the years 2009, 2012 and 2014. Subsequently, these coefficients are used to reconstruct estimated TEC maps which are then compared with actual GIM-TEC by investigating their difference in normalized $L_2$ norm squared sense. The regional planar trend model provides a particularly successful representation in the years 2012 and 2014 for which the solar activity level is the dominant factor determining the TEC trend. Under low solar activity conditions of 2009, other factors such as ocean currents, temperature variations and meteorological phenomena are suspected to have a considerable effect in some regions depending on their geographic location and on seasonal trends in those regions. As an example, studies show that under the influence of the Pacific Decadal Oscillation (PDO) and Siberian High (SH), a significant cooling trend between 2004 and 2018 in autumn is observed in Eurasia, which, in conjunction with the low solar activity levels, may be related to the deviations from the actual GIM-TEC in 2009 in these regions. As solar radiation increases, however, such bottom-side forcings are masked in 2012 and 2014 and these deviations are no longer observed.