基于复杂网络和语言信息的交互式大规模群体评价方法

针对现有基于语言信息的交互式群体评价方法大多仅适用于中小规模群体的情况,提出一种新的基于复杂网络和语言信息的交互式大规模群体评价方法。首先,将评价者视为网络节点,并依据节点之间的距离构建复杂网络;其次,设计节点紧密度和子群紧密度,并确定节点权重和子群权重;再次,定义群体稳定性指标和群体满意度指标,并以此来判断交互终止和确定阶段权重;最后,在节点密度算子和节点加权算子的基础上,分别对单轮群体意见和多轮评价结果进行集结。文末通过一个实际例子验证了所提方法的有效性与合理性。实例分析表明,该方法能够较为全面、准确地集结交互式大规模群体评价意见,且其结果的满意度亦较为理想。     

同伦分析方法中辅助算子L之选择

本文通过李对称的理论给出了同伦分析方法中选取辅助线性算子L的一个方法．     

论英语使役结构与“投射”

基于系统功能语言学对英语使役结构的相关研究以及"投射"理论.本文对"以施动者为中心"的英语使役结构与投射结构进行了辨析讨论.通过分析,我们发现,两者紧密相连而又有相异之处.由情感使役动词(如frighten)、使役关系动词(如guarantee)、认知使役动词(如remind)体现过程的使役结构可包含事实嵌入投射或主从观点投射充当结构成分,但另一方面,这些类型的使役结构又与主从述说投射结构相区别;我们需根据"使因"成分以及结构所在的上下文对使役意义的表达做出正确判断.     

算子方程A~nX(A~*)~n=B的解

利用算子矩阵分块技巧,在算子A值域闭的情况下研究了算子方程AnX(A*)n=B的解及正解的存在性,最后给出了正解的一般结构.     

Using intersection matrices to identify graphical structure

Intersection matrices help identify the common graphical structure of two or more objects. They arise naturally in a variety of settings. Several examples of their use in a computer algebra environment are given. These include: simplifying an expression involving array products, automating cumulant calculations, determining the behaviour of an expected value operator and identifying model hierarchy in a factorial experiment. The emphasis is placed on the graphical structure, and the symmetry of arrays help reduce the complexity of the graphical problem.     

Projection‐Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not applicable or is very unreliable in models with identification problems or weak instruments. One possible way out consists of using a variant of the Anderson–Rubin ((1949), AR) procedure. The latter allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, but not for individual coefficients. This problem may in principle be overcome by using projection methods (Dufour (1997), Dufour and Jasiak (2001)). At first sight, however, this technique requires the application of costly numerical algorithms. In this paper, we give a general necessary and sufficient condition that allows one to check whether an AR‐type confidence set is bounded. Furthermore, we provide an analytic solution to the problem of building projection‐based confidence sets from AR‐type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are needed to build the confidence intervals.     

关于弱化缓冲算子序列的研究

本文以预测过程中常常出现的冲击扰动问题为出发点,在灰色系统理论缓冲算子公理体系下,构造了一类弱化缓冲算子序列,对现有的弱化缓冲算子进行了整合,研究了这类弱化缓冲算子定义的内涵,实例验证了该算子序列的有效性和实用性,为解决冲击扰动系统在建模预测过程中出现的定量预测结果与定性分析结论不符的问题提供了可以借鉴的方法。     

含m-增生算子的非线性方程带误差的迭代程序

证明了对任意Banach空间E中的Lipschitz m-增生算子T,(A)f∈E.带误差的Ishikawa型迭代程序强收敛于方程x+Tx=f的唯一解.作为直接的应用,给出了有关Ishikawa迭代程序稳定性的若干定理.所得的结论改进和推广了近期相关的结果.     

算子中立型泛函微分方程等度渐近稳定性

定义了算子D的等度渐近稳定 ,并进而得到比文 [1]好的等度渐近稳定性判据。     

具有不同偏好网络结构的群体评价信息集结方法

以评价者为节点,评价者之间偏好相似性测度为连接的网络为群体偏好网络,讨论了评价群体在偏好网络均衡状态时3种不同网络结构(星形网络、闭链结构和完整网络)的群体评价信息集结方法,将具有网络结构信息的节点数据转化为平面数据,提出了平面密度加权平均算子和平面密度加权几何平均中间算子。给出了平面数据的划分方法及平面密度算子的趋同性测度,并将算子应用于各网络结构的评价群体评价问题。