基于错误逻辑分解转化联结词的生态文明指标知识表达模型研究

研究错误逻辑的知识表达模型,以错误逻辑理论结合生态文明"五位一体"所构建的生态文明建设指标体系,进行基于对象识别的知识表达.指标体系内的各元素分别被定义为错误逻辑模型中的事物、特征、函数和规则.建模时,首先进行事物分解,第二步进行特定事物下对应的特性及规则分解,最后根据判别规则G对错误函数f形式的影响,对各项指标所适用的错误函数类型进行分类.对象的生成可以为用矩阵这样的数据结构对逻辑知识进行系统化组织做前期准备.     

基于空间错误逻辑变量未知的对象识别状态与应该状态之间的转化

讨论了在错误逻辑变量中,论域、事物、特征、量值等参数为确定常量的条件下,讨论空间参数为变量且未知时,错误的识别状态转化为应该状态的方程及其求解。研究发现,当对象识别状态当前的空间包含于应该状态当前的空间时,可以采用错误矩阵一类5集合方程A∧X_(qg)?B_g构建错误矩阵集合方程求解;当对象应该状态当前的空间包含于识别状态当前的空间时,可以采用错误矩阵一类4集合方程A∨X_(qg)?B_g构建一元置换变换错误矩阵集合方程,求解识别状态和应该状态的转化。     

基于论域和量值二类错误逻辑变量求解的识别对象状态转化及其决策应用研究

研究了空间事物特征为确定常量的条件下,论域和量值参数为变量且未知时,错误识别对象状态的转化.研究发现,当对象识别状态的论域和量值都为Ⅱ类时,可以采用错误矩阵一类4集合方程A_s∨X_(qg)■B_g构建二元置换变换错误矩阵集合方程,将错误的对象识别状态转化为应该状态.最后,通过生产决策的实例说明其实际决策应用价值.     

基于特征和量值为变量时错误识别对象状态转化及其决策应用研究

文中研究了空间,论域,事物为确定常量的条件下,特征和量值参数为变量且未知时,错误识别对象状态的转化。研究发现,当对象识别状态的特征和量值为Ⅱ类时,可以采用错误矩阵一类4集合方程A_s∨X_(qg)?B_g构建二元置换变换错误矩阵集合方程,将错误的对象识别状态转化为应该状态。最后,通过实例说明其实际决策应用价值。     

基于错误逻辑相似变换构建网购用户评价有效集模型

基于错误逻辑相似转化联结词,给出了错误逻辑命题的论域、事物、空间、特征、量值、错误值、规则、错误函数、时间等参数的相似变换矩阵定义.文中给出了形式上为T(C_1)=C_2的相似变换错误矩阵方程模型.针对电子商务网购用户评价的网上抓取数据,定义了从包含若干无效评价的大集合向有效小集合变换的错误矩阵模型.模型是基于错误逻辑理论,从已知转化系数矩阵T,以及初始错误矩阵,向未知目标集合进行相似变换的知识推理探索.     

基于矩阵逻辑方程的识别对象状态转化研究

进行错误识别,首先我们需要研究识别的对象.因此,研究首先将错误识别对象分为识别状态、真是状态、应该状态和目标状态等四种状态,并且讨论了几种类型之间的关系.最后运用矩阵逻辑方程求解了识别状态转化为目标状态的转化方式.     

二类5包含型错误矩阵集合方程求解研究

在错误矩阵的基础上,提出了错误矩阵方程的类型.研究了当构成错误矩阵的元素是集合,且对于矩阵的每一行又恰好是一个错误逻辑命题的分解,这一类错误矩阵方程解的存在性,求解的方法等,并通过实例加以论证说明.     

二类1错误矩阵方程增优置换变换求解及其在城市交通管理中的应用研究

消错学的错误矩阵可表达错误逻辑里所定义的分解、相似、增加、置换、毁灭、单位变换等转化词,针对其中的置换变换,构建了二类1错误矩阵方程增优置换变换错误矩阵方程,并讨论了该类错误矩阵方程的求解.用交通管理问题对错误矩阵进行了举例,并构建相应的错误矩阵方程,利用上述的求解方法,对二类1方程置换变换进行了求解.     

基于模糊错误逻辑的投资结构优化研究

主要研究模糊错误逻辑的运算,设定了模糊错误逻辑的基本运算规则,对模糊错误逻辑公式、变量、真值、函数、字、子句、字组等概念进行定义,在此基础上,提出2个定理并予以证明,揭示了模糊错误逻辑在错误的传递、转化与消除过程中的运算规律和性质 ,然后建立了优化投资结构模糊错误逻辑模型.     

逻辑命题分解变换与模糊错误矩阵包含型集合方程求解研究

在前期研究的基础上,对错误矩阵的概念作一个介绍,在此基础上,且对于矩阵的每一行又恰好是一个模糊错误逻辑命题.因为构成这类模糊错误矩阵的元素是集合,所以这类模糊错误矩阵之间一般是集合关系式,而不只是通常方程的等式,研究这一类模糊错误矩阵方程解的存在性,求解的方法等是理论与实践的需要.以XA■B研究对象,研究得到模糊错误矩阵集合方程XA′=B解的存在性及给出求解的例子.     

矩阵构造法在动力模型物理参数识别中的应用

通过矩阵奇异值分解得到矩阵构造的表达式,并将其应用于动力模型物理参数识别问题.根据矩阵构造表达式的特点,可以使参数识别模型降阶,降阶后的模型与原模型之间的数学和物理性质有明确的对应关系,避免了为忽略高阶频率而采用缩聚方法造成的误差.最后,数值算例获得满意的结果.     

基于空间分解变换的模糊错误矩阵方程求解

模糊错误逻辑对现实世界的对象用(u,x)表示为((U,S(t),■T(t),L(t)),(x(t)=f((u(t),■),GU(t)),GU(t)),用模糊错误变换矩阵可以表示分解、相似、增加、置换、毁灭、单位变换等6种变换方法,本论文基于求解方程XA′=B,针对■的分解,研究了基于空间分解变换的错误矩阵方程求解。以期从矩阵方程求解的角度对错误转化规律进行探索研究。     

多输入多输出非线性最小相位系统的自适应模糊控制

针对多输入多输出非线性最小相位系统,把自适应模糊控制和自适应模糊辨识结合起来,提出了一种自适应模糊控制方案.设计辨识器用来辨识系统的未知部分;然后由跟踪误差和辨识误差给出了参数调节规律,两种误差同时调节参数改善了系统性能.模糊逻辑系统用来估计未知函数.控制方案保证了系统的稳定性,实现了有界跟踪.仿真结果表明了该方案的可行性.     

Identification of the state of a moving object by observation of geophysical fields

Problems of identification of the state of a moving object by observation of the geophysical fields are considered. To correct the errors accumulated in the inertial navigation system of the object, the extremal comparison of the information about the outer geophysical fields with the a priori information about them stored in the onboard computer is used (the correlation-extremal approach). The general principles for investigation of the systems for navigation of moving objects by the outer informational fields are described. A model of navigation by the geophysical field and a method for a priori estimation of the local informativeness of the field are suggested.     

Modal Logics of Stone Spaces

Interpreting modal diamond as the closure of a topological space, we axiomatize the modal logic of each metrizable Stone space and of each extremally disconnected Stone space. As a corollary, we obtain that S4.1 is the modal logic of the Pelczynski compactification of the natural numbers and S4.2 is the modal logic of the Gleason cover of the Cantor space. As another corollary, we obtain an axiomatization of the intermediate logic of each metrizable Stone space and of each extremally disconnected Stone space. In particular, we obtain that the intuitionistic logic is the logic of the Pelczynski compactification of the natural numbers and the logic of weak excluded middle is the logic of the Gleason cover of the Cantor space.     

Bayesian Object Identification: Variants

We present a Bayesian theory of object identification. Here, identifying an object means selecting a particular observation from a group of observations (variants), this observation (the regular variant) being characterized by a distributional model. In this sense, object identification means assigning a given model to one of several observations. Often, it is the statistical model of the regular variant, only, that is known. We study an estimator which relies essentially on this model and not on the characteristics of the “irregular” variants. In particular, we investigate under what conditions this variant selector is optimal. It turns out that there is a close relationship with exchangeability and Markovian reversibility. We finally apply our theory to the case of irregular variants generated from the regular variant by a Gaussian linear model.     

Optimal Sensor Placement Method Considering the Importance of Structural Performance Degradation for the Allowable Loadings for Damage Identification

Considering the importance of damage for the structural performance and for decreasing the identification error, this paper proposes an optimal sensor placement method based on a weighted standard deviation norm (WSDN) index. The standard deviation of the identified damage parameters is solved using the series expansion theory and probabilistic method to quantify the effect of a measurement error on damage identification. The damage estimation weight (DEW) index, which can reflect the importance of each element in the structural capabilities, is established based on a performance-damage curve. A significant DEW for a specified element indicates that the element is important for the structure and that its identification error should be small. The WSDN index is obtained from the Hadamard product of the standard deviations (SDs) and DEWs. Thus, the identification error of the entire structure is measured using the weighting coefficient. The optimal sensor placement (OSP) procedure is performed by minimizing the WSDN index. The proposed method can clearly decrease the uncertainties of the identification results for the important elements. Other OSP criteria, including the condition number, information entropy, and standard deviation norm, which aim to decrease the identification error, are discussed in this paper for comparison with the proposed method. Two numerical examples and an experiment, which pertain to the deformation performance, buckling features, and dynamic characteristics, are discussed to verify the advantages of the proposed method.