协方差结构分析中拟似然估计的对偶几何方法

本文应用几何方法研究了协方差结构分析中的拟似然估计.对于该模型引进了对偶几何,在此基础上得到了拟似然估计的二阶渐近性质.通过对偶曲率给出了拟似然估计的偏差、方差和信息损失,并且给出了反映拟观察信息和拟期望信息之间关系的一个极限定理     

协方差结构分析中拟似然估计的对偶几何方法

本文应用几何方法研究了协方差结构分析中的拟似然估计.对于该模型引进了对偶几何,在此基础上得到了拟似然估计的二阶渐近性质.通过对偶曲率给出了拟似然估计的偏差、方差和信息损失,并且给出了反映拟观察信息和拟期望信息之间关系的一个极限定理.     

指数族非线性模型的几何及渐近推断理论

对指数族非线性模型在Euclid空间建立了几何结构。在此基础上,研究了与统计曲率以及Fisher信息有关的渐近推断问题。这种几何结构可推广到更加广泛的模型;并可用于研究更多的统计问题。     

可由用户持续发展的几何自动推理平台

提出并实现了可由用户持续发展的几何自动推理平台(SGARP).它由知识库、知识编辑器、信息库、推理引擎、信息查询窗口和动态几何作图系统等六部分组成.在这个平台上,用户可以添加几何对象、谓词和规则,也可以综合使用多种推理方法进行推理.     

动态粗信息粒度矩阵的关系讨论

在前面已讨论过的静态粗信息矩阵数量特征(粒度、精度)基础上,利用动态粗糙集理论,进一步给出动态粗信息粒度矩阵的三种形式,系统地讨论了静态、动态系统的粗信息粒度矩阵的特征及其关系定理,这一研究不仅完善了粗信息矩阵这一新的研究方向内容,而且为动态系统的知识挖掘提供了一个可靠的依据。     

市场需求信息不对称下的保兑仓融资风险控制策略

信息不对称风险广泛存在于保兑仓融资过程当中,本文运用Stackelberg博弈模型刻画融资系统成员关系,运用动态规划优化分析方法求解对应博弈均衡策略。总结出需求信息不对称的三种表现形式:信息造假,信息优势及信息隐匿,分析各类信息不对称情形对融资系统所造成影响,并相应提出实现信息显示功能的契约甄别机制。研究表明:零售商可从信息不对称中获取巨大信息优势,但对其他成员造成损害,其中信息隐匿对生产商损害程度更高;二部定价机制可实现信息甄别,但生产商须为之付出信息租金,造成效率损失;而合理参数设定下的二部定价加回购机制有助于进一步改进融资系统及各成员收益,甚至达到次协调状态,最终实现融资成员收益的帕累托改进。本研究对于控制供应链融资中的信息风险、改善融资效率提供了理论依据及决策参考。     

信息融合中提高信源置信度的方法研究

在分析信息融合和模糊神经网络理论的基础上,构造出具有质量信息的模糊神经网络信息融合结构.通过模糊神经网络对信源本身、环境因素、人为因素等各种因素的处理给出各个信源的置信度因子,再将置信因子与各信源的报告数据统一进行融合处理,可提高各信源的可信度,从而提高融合系统的可靠性和有效性,使系统的整体性能加强.     

基于多目标规划的同义词替换信息隐藏模型

从含密载体这一个物理信道抽象出秘密信息和原始载体分别到含密载体的两个逻辑信道,前者关联信息隐藏容量,后者作为载体统计保真约束的系统接口,通过建立多目标规划模型来求解信息隐藏函数,使得信息隐藏函数的设计可受原始载体、秘密信息的分布以及系统统计失真指标控制.MATLAB数值实验结果说明该算(?)可以有效的寻找到最优的信息隐藏函数.     

基于非对称信息和VMI模式的供应链协调模型

在假定分销商允许缺货发生和供应商控制库存的前提下,建立了一类供应——分销型供应链在对称信息和非对称信息这两种情况下的生产库存协调模型,给出了相应的最优协调策略,并通过比较对称信息与非对称信息下系统的总费用,揭示了信息对称与否对协调策略及系统总费用的影响.     

一道图像信息试题的命制、实践及感悟

图像信息类试题是近年中考的热点问题,往往通过图像形状、点的位置以及变化趋势等来呈现信息,侧重考查从现实背景中分析问题、解决问题能力以及数学思想方法的灵活应用,考查学生建立的数感和符号意识,形成模型意识,体现“问题情景-建立模型-解释、应用和拓展”的数学学习模式．解题关键“识图”和“用图”,需充分发掘图像所蕴含的信息,利用函数、方程（组）、不等式及几何知识来解决问题,并从中体会、感悟所蕴涵的思想方法．     

Computationally tractable pairwise complexity profile

Quantifying the complexity of systems consisting of many interacting parts has been an important challenge in the field of complex systems in both abstract and applied contexts. One approach, the complexity profile, is a measure of the information to describe a system as a function of the scale at which it is observed. We present a new formulation of the complexity profile, which expands its possible application to high‐dimensional real‐world and mathematically defined systems. The new method is constructed from the pairwise dependencies between components of the system. The pairwise approach may serve as both a formulation in its own right and a computationally feasible approximation to the original complexity profile. We compare it to the original complexity profile by giving cases where they are equivalent, proving properties common to both methods, and demonstrating where they differ. Both formulations satisfy linear superposition for unrelated systems and conservation of total degrees of freedom (sum rule). The new pairwise formulation is also a monotonically nonincreasing function of scale. Furthermore, we show that the new formulation defines a class of related complexity profile functions for a given system, demonstrating the generality of the formalism. © 2013 Wiley Periodicals, Inc. Complexity 18:20–27, 2013     

From big data to important information

Advances in science are being sought in newly available opportunities to collect massive quantities of data about complex systems. While key advances are being made in detailed mapping of systems, how to relate these data to solving many of the challenges facing humanity is unclear. The questions we often wish to address require identifying the impact of interventions on the system and that impact is not apparent in the detailed data that is available. Here, we review key concepts and motivate a general framework for building larger scale views of complex systems and for characterizing the importance of information in physical, biological, and social systems. We provide examples of its application to evolutionary biology with relevance to ecology, biodiversity, pandemics, and human lifespan, and in the context of social systems with relevance to ethnic violence, global food prices, and stock market panic. Framing scientific inquiry as an effort to determine what is important and unimportant is a means for advancing our understanding and addressing many practical concerns, such as economic development or treating disease. © 2016 Wiley Periodicals, Inc. Complexity 21: 73–98, 2016     

集值信息系统及其属性约简

阐明集值信息系统具有知识表达的实际意义;引入关于相容关系的最大相容分类方法对论域中的对象分类,以保证每个相容类中的对象具有共同的属性特征;讨论集值信息系统的属性约简问题,利用区分函数,给出核及约简的求法.     

Quantity of information; Comparison between information systems: 1. Non-fuzzy states

In statistical theory, experiments or probabilistic information systems are supposed to be informative, since they reduce the amount of uncertainty associated with the states of nature. For the case that the available information systems are vague (fuzzy information systems), H. Tanaka, T. Okuda and K. Asai have proven, using the ‘measure of information’ as provided by ‘entropy’, that the fuzzy information systems are informative too.Now, we wish to state and to study a criterion in order to compare fuzzy information systems by the ‘quantity of information of a fuzzy information system’ (defined by Tanaka et al.).In this first paper we consider the situation where we require information about the original state space (non-fuzzy state space).The second paper will deal with the situation where we require only information on certain vague states (fuzzy states).     

Quantity of information; comparison between information systems: 2. Fuzzy states

In statistical theory, experiments or probabilistic information systems are supposed to be informative, since they reduce the amount of uncertainty associated with the states of nature. For the case that the available information systems are vague (fuzzy information systems), H. Tanaka, T. Okuda and K. Asai have proven, using the ‘measure of information’ as provided by ‘entropy’, that the fuzzy information systems are informative too.Now, we wish to state and to study a criterion in order to compare fuzzy information systems by the ‘quantity of information of a fuzzy information system’ (defined by Tanaka et al.).In the first paper we considered the situation where we require information about the original state space (non-fuzzy state space).This second paper deals with the situation where we require only information on certain vague states (fuzzy states).     

相依非线性回归系统中的附加信息Bayes拟似然

对多个相依统计模型的研究,现有成果主要集中在相依线性回归系统.本文则首次提出多个相依非线性回归系统中的附加信息Bayes拟似然,给出误差相关信息和先验信息在拟似然中的迭加方法,在较弱的条件下得到附加信息Bayes拟似然的一些性质,在Bayes风险准则下。讨论了其估计函数和参数估计的最优性,证明了附加信息Bayes拟似然的渐近 Bayes风险随着相依信息的增力。而逐步减少.     

The limits of phenomenology: From behaviorism to drug testing and engineering design

It is widely believed that theory is useful in physics because it describes simple systems and that strictly empirical phenomenological approaches are necessary for complex biological and social systems. Here, we prove based on an analysis of the information that can be obtained from experimental observations that theory is even more essential in the understanding of complex systems. Implications of this proof revise the general understanding of how we can understand complex systems including the behaviorist approach to human behavior, problems with testing engineered systems, and medical experimentation for evaluating treatments and the Food and Drug Administration approval of medications. Each of these approaches are inherently limited in their ability to characterize real world systems due to the large number of conditions that can affect their behavior. Models are necessary as they can help to characterize behavior without requiring observations for all possible conditions. The testing of models by empirical observations enhances the utility of those observations. For systems for which adequate models have not been developed, or are not practical, the limitations of empirical testing lead to uncertainty in our knowledge and risks in individual, organizational, and social policy decisions. These risks should be recognized and inform our decisions. © 2015 Wiley Periodicals, Inc. Complexity 21: 181–189, 2016     

Fisher information under restriction of Shannon information in multi-terminal situations

Fisher information generally decreases by summarizing observed data into encoded messages. The present paper studies the amount of Fisher information included in independently summarized messages from correlated information sources; that is, the amount of Fisher information when sequences x ^N and y ^N of N independent observations of random variables x and y are encoded (summarized) independently of each other into meassages m _X and m _Y . The problem is to obtain the maximal amount of Fisher information when the size of the summarized data or Shannon message information is limited. The problem is solved in the case of completely compressed symmetric data summarization. An achievable bound is given in the general case. Information geometry, which is a powerful new differential geometrical method applicable to statistics and systems theory, is applied to this problem, proving its usefulness in information theory as well.The present work is supported in part by Grant-in-Aid for Scientific Research #61030014, Ministry of Education, Science and Culture of Japan.     

信息系统的价值体系耦合规划

许多企业正在进行信息集成,运用耦合规划建立企业业务活动到信息系统的联结模型,采用类似于对策理论技术的协商方法对多信息系统协作求解.     

Data compression with homomorphism in covering information systems

In reality we are always faced with a large number of complex massive databases. In this work we introduce the notion of a homomorphism as a kind of tool to study data compression in covering information systems. The concepts of consistent functions related to covers are first defined. Then, by classical extension principle the concepts of covering mapping and inverse covering mapping are introduced and their properties are studied. Finally, the notions of homomorphisms of information systems based on covers are proposed, and it is proved that a complex massive covering information system can be compressed into a relatively small-scale information system and its attribute reduction is invariant under the condition of homomorphism, that is, attribute reductions in the original system and image system are equivalent to each other.