GRP文件格式到MIF格式的实现

为将ＧＲＰ文件格式转换成ＭＩＦ文件格式，提供一种数据不变，而文件存储方式改变的数据转换方法和实例。     

一种基于浑沌理论的联想记忆神经网络模型

根据联想记忆神经网络的基本原理，提出了一种基于浑沌理论的联想记忆神经网络模型及相应的求解方案，并对该种模型进行了预报试验。结果表明，该种模型的历史预报准确率和实际预报准确率均超过一般随机预报，值得进一步研究和应用。     

计算机内存的分类及优化管理

本文从计算机应用角度出发，介绍了计算机内存的基本结构及其类型内存配置对计算机工作的影响，同时讨论了如何合理计算机内存，以便充分发挥计算机的优势。     

SMA-MR复合型阻尼器

利用形状记忆合金超弹性、形状记忆特性和MR液的材料特性，提出了SMA-MR复合阻尼器，建立了阻尼器的理论模型。通过输入正弦波得到小震、大震时相应的滞回曲线，并对一单层框架进行输入El Centro地震波下的减震效果分析，比较了SMA-MR阻尼器、仅有SMA和仅有MR作用下的减震效果。结果表明，所设计的SMA-MR阻尼器具有卓越的阻尼性能，对大震、小震的控制实现了自适应的智能性。     

岩石Kaiser效应测地应力原理中的若干问题研究

该文通过对几种不同类型岩石的实验研究，提出了关于在围压条件下影响岩石Kaiser效应的若干问题，分析了它们的声发射特征，为深部地应力测量提供了一种新的解决方法。     

Knowledge Representation Methods in Expert System for Earthquake Prediction ESEP 3.0

INTRODUCTIONKnowledgerepresentationandknowledgeacquisitionarekeyissuesinbuildinganexpertsystem .Theyarecloselyrelatedtothedomainproblem solvinglevelandcompetenceoftheexpertsystem .Intheknowledgeacquisitionprocess,thedomainexpertwillfirstofferandorganizepr…     

The effects of visual realism,spatial abilities,and competition on performance in map-based route learning in men

We report on how visual realism might influence map-based route learning performance in a controlled laboratory experiment with 104 male participants in a competitive context. Using animations of a dot moving through routes of interest, we find that participants recall the routes more accurately with abstract road maps than with more realistic satellite maps. We also find that, irrespective of visual realism, participants with higher spatial abilities (high-spatial participants) are more accurate in memorizing map-based routes than participants with lower spatial abilities (low-spatial participants). On the other hand, added visual realism limits high-spatial participants in their route recall speed, while it seems not to influence the recall speed of low-spatial participants. Competition affects participants’ overall confidence positively, but does not affect their route recall performance neither in terms of accuracy nor speed. With this study, we provide further empirical evidence demonstrating that it is important to choose the appropriate map type considering task characteristics and spatial abilities. While satellite maps might be perceived as more fun to use, or visually more attractive than road maps, they also require more cognitive resources for many map-based tasks, which is true even for high-spatial users.     

基于小波长短期记忆网络的风电功率超短期概率预测

随着大规模的风电并网,风电所具有的间歇性与随机性对电力系统的稳定性产生了很大的影响,风电功率预测成为当前解决该问题重要的方式之一.本文利用长短期记忆（LSTM）网络良好的时序记忆特性,将小波分解技术与LSTM深度网络结合,提出基于小波长短期记忆网络的风电功率超短期概率预测模型.首先通过小波分解技术将原始时间序列进行平稳化处理,再建立各子序列样本的LSTM网络预测模型,借助最大似然估计法估计预测误差的高斯分布函数,最终实现对未来4 h时刻的风电功率概率区间预测.最后,采用中国东北某风电场数据对所提方法进行算例分析,结果表明,将小波分解与深度学习方法结合可以较好地提高预测的精度,提高概率预测的区间可靠性.