现有基于神经网络的电池荷电状态(state of charge,SOC)预测研究大多把重点放在模型结构和相关参数的优化上,却忽略了训练数据的重要作用.针对该问题,文中提出了一种基于特征选择和数据增强的电池SOC预测方法.首先,方法根据原始电池充...现有基于神经网络的电池荷电状态(state of charge,SOC)预测研究大多把重点放在模型结构和相关参数的优化上,却忽略了训练数据的重要作用.针对该问题,文中提出了一种基于特征选择和数据增强的电池SOC预测方法.首先,方法根据原始电池充放电数据进行特征工程,并使用排列重要性(permutation importance,PI)方法选出对模型预测最有帮助的7个特征;其次,通过加入高斯噪声来扩大训练数据样本总量,达到数据增强的目的.实验使用双向长短时记忆网络(bidirectional long short-term memory,Bi-LSTM)作为预测模型,使用Panasonic 18650PF数据集作为训练数据.使用标准Bi-LSTM进行预测时,平均绝对误差(mean absolute error,MAE)和最大误差(max error,MaxE)分别为0.65%和3.92%,而在进行特征选择和数据增强后,模型预测的MAE和MaxE分别为0.47%和2.62%,表明PI特征工程与高斯数据增强方法可以进一步提升电池荷电状态预测模型的精度.展开更多
目的:探讨CD44与CD33在口腔黏膜良性淋巴组织增生病(benign lymphoadenosis of oral mucosa,BLOM)中的表达及临床意义。方法:选择2017年1月—2020年3月青岛市中医医院病理科77例BLOM蜡块作为实验组,另取同时间段63例正常口腔黏膜组织蜡...目的:探讨CD44与CD33在口腔黏膜良性淋巴组织增生病(benign lymphoadenosis of oral mucosa,BLOM)中的表达及临床意义。方法:选择2017年1月—2020年3月青岛市中医医院病理科77例BLOM蜡块作为实验组,另取同时间段63例正常口腔黏膜组织蜡块作为对照组。采用免疫组织化学法检测2组CD44、CD33阳性表达情况,采用Spearman分析BLOM患者病变组织中CD33与CD44阳性表达的相关性。收集患者一般资料,分析BLOM患者病变组织中CD33、CD44表达与临床病理特征的关系。采用SPSS 21.0软件包对数据进行统计学分析。结果:对照组、实验组CD33阳性表达率分别为95.24%、63.64%,差异有统计学意义(P<0.05);CD44阳性表达率分别为93.65%、67.53%,差异有统计学意义(P<0.05)。Spearman分析结果显示,BLOM患者病变组织中CD33与CD44阳性表达呈正相关(r=0.834,P=0.002);CD33、CD44表达与临床分型、炎症程度、有无淋巴滤泡、淋巴细胞浸润有关(P<0.05),而与年龄、性别、病程、病变部位、上皮表面角化无关(P>0.05)。结论:BLOM患者病变组织中CD33、CD44阳性表达率下降,与临床分型、炎症程度、有无淋巴滤泡、淋巴细胞浸润密切相关。展开更多
A problem of topology identification for complex dynamical networks is investigated in this paper. An adaptive observer is proposed to identify the topology of a complex dynamical networks based on the Lyapunov stabil...A problem of topology identification for complex dynamical networks is investigated in this paper. An adaptive observer is proposed to identify the topology of a complex dynamical networks based on the Lyapunov stability theory. Here the output of the network and the states of the observer are used to construct the updating law of the topology such that the communication resources from the network to its observer are saved. Some convergent criteria of the adaptive observer are derived in the form of linear inequality matrices. Several numerical examples are shown to demonstrate the effectiveness of the proposed observer.展开更多
In this paper, we study the epidemic spreading in scale-flee networks and propose a new susceptible-infected- recovered （SIR） model that includes the effect of individual vigilance. In our model, the effective sprea...In this paper, we study the epidemic spreading in scale-flee networks and propose a new susceptible-infected- recovered （SIR） model that includes the effect of individual vigilance. In our model, the effective spreading rate is dynamically adjusted with the time evolution at the vigilance period. Using the mean-field theory, an analytical result is derived. It shows that individual vigilance has no effect on the epidemic threshold. The numerical simulations agree well with the analytical result. Purthermore, we investigate the effect of individual vigilance on the epidemic spreading speed. It is shown that individual vigilance can slow the epidemic spreading speed effectively and delay the arrival of peak epidemic infection.展开更多
基金supported in part by the National Natural Science Foundation of China (Grant Nos.60874091 and 61104103)the Natural Science Fund for Colleges and Universities in Jiangsu Province,China (Grant No.10KJB120001)the Climbing Program of Nanjing University of Posts & Telecommunications,China (Grant Nos.NY210013 and NY210014)
文摘A problem of topology identification for complex dynamical networks is investigated in this paper. An adaptive observer is proposed to identify the topology of a complex dynamical networks based on the Lyapunov stability theory. Here the output of the network and the states of the observer are used to construct the updating law of the topology such that the communication resources from the network to its observer are saved. Some convergent criteria of the adaptive observer are derived in the form of linear inequality matrices. Several numerical examples are shown to demonstrate the effectiveness of the proposed observer.
基金Project supported by the National Natural Science Foundation of China(Grant No.60874091)the Six Projects Sponsoring Talent Summits of Jiangsu Province,China(Grant No.SJ209006)+1 种基金the Natural Science Foundation of Jiangsu Province,China(Grant No.BK2010526)the Graduate Student Innovation Research Project of Jiangsu Province,China(Grant No.CXLX110417)
文摘In this paper, we study the epidemic spreading in scale-flee networks and propose a new susceptible-infected- recovered （SIR） model that includes the effect of individual vigilance. In our model, the effective spreading rate is dynamically adjusted with the time evolution at the vigilance period. Using the mean-field theory, an analytical result is derived. It shows that individual vigilance has no effect on the epidemic threshold. The numerical simulations agree well with the analytical result. Purthermore, we investigate the effect of individual vigilance on the epidemic spreading speed. It is shown that individual vigilance can slow the epidemic spreading speed effectively and delay the arrival of peak epidemic infection.
