基于贯序正则极端学习机的时间序列预测及其应用

为实现对液压泵特征参数的在线预测,提出一种贯序正则极端学习机(SRELM),并研究了基于SRELM的预测方法.SRELM根据结构风险最小化原理实现网络训练,其网络权值可随新样本的逐次加入而递推求解,具有泛化能力强与训练速度快的优点,因此适于特征参数的在线预测.基于SRELM的预测方法利用特征参数训练SRELM模型,以逐...     

基于Webservice的个别指导式远程学习软件及知识设计策略

建构个别指导式远程学习软件的系统模型,根据认知心理学领域,知识分为陈述性知识和程序性知识,主要讨论知识库模型中,针对不同的知识选择不同的设计策略,以增加软件的可读性,使学生能进行高效率地学习.     

中国学生学习动机研究述评

以中国学生学习动机研究的文献为基础,对学生学习动机研究方法,学生学习动机的现状,学生学习动机的影响因素,学生学习动机与其他因素的关系等方面进行了回顾,展望了该领域的研究方向,为学生学习动机的深入研究提供借鉴.     

基于深度学习的SAR图像质量提升方法研究

提升合成孔径雷达(SAR)图像质量以增强其可判读性,一直是SAR图像处理中的关键问题。近年来,深度学习在光学图像处理中取得显著的成功,并逐步应用到SAR图像质量提升领域。对深度学习在SAR图像质量提升中的关键应用进行综述,对深度学习在SAR图像质量提升中采用的典型网络进行了介绍,并从SAR图像旁瓣抑制、超分辨(SR)处理和图像融合3个方面对深度学习的应用进行阐述。最后,分析与探讨了基于深度学习的SAR图像质量提升中的关键问题及进一步研究方向。     

从王国维谈人文素质

撷王国维博大深沉学术之一粟,试对王国维所蕴含和阐发的人文素质做一个简约的梳理,以期窥其特质,集心香一瓣,并引为今人启迪。     

Perception,object kind,and object naming

Spatial Cognition and Computation - We investigated whether certain perceptual properties of objects could support children's and adults' judgments of the range of shape changes permissible...     

Age differences in adults' spatial abilities,learning environmental layout,and wayfinding behavior

Empirical relations among age, general spatialability as assessed by psychometric tests,wayfinding-related skills as assessed byexperimental tasks in the laboratory,environmental layout learning as assessed in afield experiment, and wayfinding behavior asobserved in a field experiment were modeled ina study involving 120 younger and 120 olderadults. The best-fitting model showed thatage-related differences in learningenvironmental layout were significantly, butnot exclusively, mediated by a single abilityfactor defined by psychometric tests. Knowledge of environmental layout was theexclusive mediator between general spatialability and wayfinding behavior. Thus, agedifferences in psychometric test performancewere found to be a major factor in accountingfor aging-related decline in learningenvironmental layout, but other variables notassessed in this study also play a significantrole.     

在大学综合英语课堂教学中提升学生学习自主性的行动研究

通过采用行动研究的方法,揭示大学生英语学习中自主性问题的现状,并试图在教学实践中探索出有效的提升大学生英语学习自主性的方法。通过问卷、访谈、课堂观察等方式展开调查,并在分析和实践中发现,只有教师不断地激励,并在课堂上创设能够让学生发挥学习自主性的情境,开展多样的课堂活动,学生的英语学习自主性才会不断地提升,英语学习才会呈现出良性发展的态势。     

Measuring air traffic complexity based on small samples

Air traffic complexity is an objective metric for evaluating the operational condition of the airspace.It has several applications,such as airspace design and traffic flow management.Therefore,identifying a reliable method to accurately measure traffic complexity is important.Considering that many factors correlate with traffic complexity in complicated nonlinear ways,researchers have proposed several complexity evaluation methods based on machine learning models which were trained with large samples.However,the high cost of sample collection usually results in limited training set.In this paper,an ensemble learning model is proposed for measuring air traffic complexity within a sector based on small samples.To exploit the classification information within each factor,multiple diverse factor subsets (FSSs) are generated under guidance from factor noise and independence analysis.Then,a base complexity evaluator is built corresponding to each FSS.The final complexity evaluation result is obtained by integrating all results from the base evaluators.Experimental studies using real-world air traffic operation data demonstrate the advantages of our model for small-sample-based traffic complexity evaluation over other stateof-the-art methods.     

基于深度学习的ADS-B异常数据检测模型

广播式自动相关监视（ADS-B）是下一代空中交通运输系统的重要组成部分，是新航行系统中非常重要的通信和监视技术，但其协议没有提供相关的信息认证和数据加密，因此极其容易受到欺骗干扰的影响。针对ADS-B报文数据特点，采用深度学习的seq2seq模型对ADS-B报文数据进行重构，通过重构误差来检测异常，并对数据进行特征扩展，使模型能更好的捕捉数据的时间依赖性。实验结果表明，所采用的方法优于传统的机器学习方法，且在数据特征扩展后，模型检测效果提升。相比于现有的欺骗干扰检测方法，该方法不需要改变ADS-B系统的协议，也不需要额外的节点或传感器参与，具有一定的适应性和灵活性。