关于信息技术与未来战争若干问题的思考

每个时代的战争都有自己的技术基础。技术基础不同 ,战争的形态、样式、特点也不同。人类已经经历了农业时代的冷兵器战争 ,近代的热兵器战争以及工业时代的机械化战争。随着信息技术的发展及广泛应用 ,信息化战争将逐步取代工业时代的机械化战争 ,在信息化武器、软件信息武器、C4I系统的支持下 ,呈现出制信息权、非线式战场、脱离接触的战斗等一些新特点 ,战争中信息的收集、传播与处理能力成为决定战争胜负的重要因素     

基于小波分析的石油价格长期趋势预测方法及其实证研究

本文将小波方法引入到油价长期趋势的预测中,利用小波多尺度分析的功能,提出了一种可以较为准确地根据油价时序列预测其未来长期走势的方法。这种方法的优点在于可以准确地提取油价的长期趋势,从总体上把握油价的非线性波动特征,从而能够很好地利用油价时间序列的历史数据,开展对未来一段时期内的多步预测。实证研究中,对Brent油价开展了时间跨度为1年的趋势预测,并将预测结果与ARIMA、GARCH、Holtwinters等方法得到的结果进行了比较,表明了基于小波分析的长期趋势预测法的预测能力是其他方法所不能比拟的,反映了本文所建立的石油价格长期趋势预测方法的有效性。     

技术创新的复杂性思考

技术创新是当代技术进步的重要源泉,是知识经济时代的主要标志。技术创新复杂性是近年来关心技术创新和管理组织建设的学者提出的概念。从非线性思维视角分析了技术创新的定义及组织过程,在对技术创所具有的整体性、不确定性及非线性等特点进行阐述的基础上,指出了技术创新是个复杂的系统过程。对技术创新的层次、内部非线性作用、自组织性及其演化性进行了辨析,为技术创新的研究方法提供了一个新的视域。     

Online monitoring of high-dimensional binary data streams with application to extreme weather surveillance

With the rapid development of modern sensor technology, high-dimensional data streams appear frequently nowadays, bringing urgent needs for effective statistical process control (SPC) tools. In such a context, the online monitoring problem of high-dimensional and correlated binary data streams is becoming very important. Conventional SPC methods for monitoring multivariate binary processes may fail when facing high-dimensional applications due to high computational complexity and the lack of efficiency. In this paper, motivated by an application in extreme weather surveillance, we propose a novel pairwise approach that considers the most informative pairwise correlation between any two data streams. The information is then integrated into an exponential weighted moving average (EWMA) charting scheme to monitor abnormal mean changes in high-dimensional binary data streams. Extensive simulation study together with a real-data analysis demonstrates the efficiency and applicability of the proposed control chart.     

Seasonal patterns of global oil consumption: Implications for long term energy policy

The dynamic evolution of the seasonal patterns in world oil consumption is dictated by complex interactions between regional consumers. Although this global pattern was stable and predictable in the past, recently it has undergone dramatic changes that have not been well understood yet. This paper contributes to literature on oil consumption behaviours by analysing the counter-balance of ‘coincident’ and ‘counter-directional’ regional seasonal patterns that have time-varying amplitude relative to their longer-term trends. It is shown that the recent global seasonal changes have been mainly driven by long-run demand trends in fast-growing emerging markets and, to a lesser extent, by idiosyncratic changes in regions’ seasonal amplitude. Our analysis is relevant to energy policy in general as both global and regional oil consumption seasonality have important implications for oil pricing, investment decisions, hedging, geopolitics and energy security.     

拓扑度理论中一个引理的改进

本文对文献（１）的一个引理进行了改进，从而推知拓扑度理论具有严密的逻辑性。     

小波级数变换的一种离散小波变换算法

小波文献中，离散小波变换多由于带分解或拉普拉斯塔形分解等引出。本文从连续小波变换及小波级数变换出发，通过对采样过程的分析导出了离散小波变换的定义。离散小波变换是唯一便于Ｘ数值计算的小波变换，本文提出了一种以离散小波变换计算小波级数变换的算法，该算法较之Ｏ’Ｒｌｏｕｌ的类似算法相比，可取得更好的计算精度。     

Statistical analysis of a portable parallel non-linear programming algorithm

It is well known that the availability of cost-effective and powerful parallel computers has enhanced the ability of the operations research community to solve laborious computational problems. But many researchers argue that the lack of portability of parallel algorithms is a major drawback to utilizing parallel computers. This paper studies the performance of a portable parallel unconstrained non-gradient optimization algorithm, when executed in various shared-memory multiprocessor systems, compared with its non-portable code. Analysis of covariance is used to analyse how the algorithm's performance is affected by several factors of interest. The results yield more insights into the parallel computing.     

基于虚拟仪器的机车滚动轴承故障诊断研究

介绍了机车滚动轴承故障诊断的机理。利用LabVIEW软件和相关硬件，设计了一种机车滚动轴承故障诊断系统。该系统结合某一型号机车轮对，利用CompactDAQ和NI 9233加速度采集模块采集滚动轴承振动信号。根据滚动轴承机理，振动信号包含滚动轴承故障信息。因此，运用小波变换函数，对振动信号进行时频域分析处理，获取有用的故障特征信息，进而确定故障类型。从实验结果可以看出，该方法能准确地找到故障频率，对于机车滚动轴承故障诊断有很好的指导意义     

使用小波分析的图像融合算法

利用小波分析实现ＳＡＲ图像与光学图像的融合和互补性。这种图像融合方法是利用ＳＡＲ图像小波分解后的近似部分和光学图像小波分解后的细节部分，组成一个新的小波分解系数，再进行逆小波变换（重构），即可得到复合的图像，取得了较好的实验效果。