基于奇异谱分析的我国航空客运量集成预测模型

针对时间序列包含噪声以及单一模型可能存在预测表现不稳定的问题,本文提出了一个基于奇异谱分析(SSA)的集成预测模型,并将其运用于我国年度航空客运量的预测中.首先,采用SSA方法对原始时间序列进行分解和重构,得到一个剔除噪声的时间序列,然后将其作为单整自回归移动平均模型(ARIMA)、支持向量回归模型(SVR)、Holt-Winters方法(HW)等单一模型的输入并进行预测,接着再采用加权平均集成预测方法(WA)将三种单一模型的预测结果进行综合集成.通过与各单一模型、基于经验模态分解方法(EMD)的模型以及简单平均集成预测方法(SA)的预测结果进行对比发现,本文所建模型具有较高的预测精度和较稳定的预测表现.最后,采用本文的模型对我国2014-2016年年度航空客运量进行了预测.     

A DEA-TOPSIS method for multiple criteria decision analysis in emergency management

A hybrid approach of DEA (data envelopment analysis) and TOPSIS (technique for order performance (preference) by similarity to ideal solution) is proposed for multiple criteria decision analysis in emergency management. Two DEA-based optimization models are constructed to facilitate identifying parameter information regarding criterion weights and quantifying qualitative criteria in TOPSIS. An emergency management case study utilizing data from the Emergency Management Australia (EMA) Disasters Database is provided to demonstrate the feasibility of the proposed analysis procedure.     

On the Gracefulness of the Digraphs n·Cm＊

A digraph D（V, E） is said to be graceful if there exists an injection f ： V（G） →{0, 1,... , ｜E｜} such that the induced function f＇ ： E（G） --~ {1, 2,… , ｜E｜} which is defined by f＇ （u, v） = [f（v） - f（u）] （rood ｜E｜＋ 1） for every directed edge （u, v） is a bijection. Here, f is called a graceful labeling （graceful numbering） of D（V, E）, while f＇ is called the induced edge＇s graceful labeling of D. In this paper we discuss the gracefulness of the digraph n- Cm and prove that n. Cm is a graceful digraph for m = 15, 17 and even     

集中式多传感器无极联合概率数据互联算法

针对杂波环境下非线性系统中的多传感器多目标跟踪问题,提出了一种集中式多传感器无极联合概率数据互联算法。该算法中,首先采用无极卡尔曼滤波器实现非线性系统中状态分布的传递,在此基础上应用联合概率数据的思想将单个传感器的量测点迹与航迹互联,最后推广至顺序结构。由于无极卡尔曼滤波器可以获得比扩展卡尔曼滤波算法更高精度的近似,因此能减少非线性模型线性化引起的近似误差对联合概率数据互联概率及状态估计的影响,与基于扩展卡尔曼滤波器思想的顺序多传感器联合概率数据互联算法相比,该算法具有更高的跟踪精度和稳定性,最后通过仿真结果验证了该算法的优越性。     

一个临界混沌系统的驱动和时滞反馈控制同步

利用驱动和时滞反馈控制的混合方法,从理论上提出了渐近同步的新标准.其中,只要设置两个控制器就能使得驱动系统和响应系统达到完全同步,而且这种同步是时滞无关的同步.最后的数值模拟也表明提出的理论结果是正确和有效的.     

基于级联卷积神经网络的港口多方向舰船检测与分类

港口舰船目标自动检测的定位和类型分类是一个重要而具有挑战性的问题。针对高分辨率光学遥感影像中多方向性排列密集的近岸舰船目标定位和识别困难的问题,提出基于级联区域卷积神经网络和手工提取特征相结合的近岸舰船检测识别框架。首先,使用级联的区域卷积神经网络对舰船位置进行粗定位并对类别进行估计,得到一系列粗定位的垂直预测框。然后,设计一个可以准确定位舰船的斜框旋转回归器,其将第一阶段所得粗定位垂直矩形框转变为带方向的斜矩形框。最后,使用非极大值抑制的方法去除冗余的预测框。实验采用谷歌地球上采集的数据集进行训练和预测,实验结果表明所提算法在精准率和召回率上均具有较大优势。     

基于CES生产函数汇率理论的FDI战略动机模型建构

运用CES生产函数建立关于FDI战略动机与汇率之间的理论模型,并对其进行求解,从而在理论上论证汇率对于两类FDI战略动机的影响以及它们之间的差异,得出结论:工资率上升都会对FDI产生负面效应;币值对于市场导向型FDI会产生正面效应、对成本导向型FDI会产生负面效应.同时得出CES生产函数汇率理论模型的投资关于汇率和工资率的弹性结果有效、客观=和合理.并通过实证分析11个经济体代表样本,运用所选实证模型,采用经过处理后的数据,用EVIWES进行线性回归后分析得出结论:外商首先最看重的是我国巨大的消费市场,其次才是利用我国廉价的劳动力和丰富的自然资源.基于目前人民币的现实和预期升值问题,提出相应对策.     

Angular glint calculation and analysis of radar targets via adaptive cross approximation algorithm

Angular glint is a significant electromagnetic （EM） scattering signature of extended radar targets. Based on the adaptive cross approximation （ACA） algorithm accelerated method of moments （MoM） and the plane incident wave assumption, the narrowband, wideband and newly developed high-resolution range profile （HRRP） based angular glint calculation formulations are derived and applied to arbitrarily shaped three-dimensional （3D） perfectly electrical y conducting （PEC） objects. In addition, the near-field angular glint is emphasized, which is of great importance for radarseeker applications. Furthermore, with the HRRP based angular glint, an approach to rigorously determine range resolution cel s which own relatively smal er angular glint is provided. Numerical results are presented with new findings to demonstrate the usefulness of the developed formulations.     

Single foggy image restoration based on spatial correlation analysis of dark channel prior

Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene.     

Information identification in different networks with heterogeneous information sources

Traditional cheaptalk game model with homogeneous information sources provided a con clusion that dishonest information sources will not be identified if he changes strategy stochastically. In this paper, the authors incorporate different information diffusion networks and heterogeneous in formation sources into an agentbased artificial stock market. The obtained results are different with traditional results that identification ability of uninformed agents has been highly improved with diffu sion networks and heterogeneous information sources. Additionally, the authors find uninformed agents can improve identification ability only if there exists a sufficient number of heterogeneous information sources in stock market.