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。     

基于错误逻辑矩阵的错误识别对象分类及应用研究

研究了错误识别对象的概念和特征,并选取七个特征组合建立了错误识别对象的错误逻辑矩阵表达式,讨论了错误识别对象的类型.最后,结合石塑地板产品质检过程,对于所进行检验的每一片石塑地板建立错误识别的对象逻辑矩阵,通过错误函数求错误值,识别错误的石塑地板对象,并根据错误石塑地板对象特征分类,采用相应的消避错方法进行运算和处理.     

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.     

经典错误逻辑的相似转化词

经典错误逻辑研究的是错误传递、转化的规律,它为决策中避免错误,消除错误,减小错误的危害提供了新的方法.相似转化词是经典错误逻辑中的一个重要转化词,定义了相似转化词的概念,研究了这个转化词所具有的性质和规律.     

消错逻辑的增加转化词

定义了增加转化词的概念 ,说明了它的研究对象及在消除决策错误中的作用 ,研究了在消错逻辑变换中 ,这个转化词所具有的性质和规律 .     

模糊错误逻辑的组合转化词分析

模糊错误逻辑研究的是错误传递、转化的规律,它为决策中避免错误,消除错误,减小错误的危害提供了新的方法.组合转化词是模糊错误逻辑中的一个重要转化词,定义了组合转化词的概念.分析了这个转化词的性质和运算规律.     

一种估算马尔柯夫状态转移概率矩阵的新方法

在现有文献研究的基础上,对马尔柯夫状态转移概率矩阵估算方法又作了进一步研究,根据马尔柯夫状态转移概率矩阵的性质和特点,提出了一种新的估算方法.方法首先构造了一个以相对误差绝对值之和最小为目标,以某一状态转移到其他状态的概率之和等于1以及状态转移概率不小于零为约束条件的优化模型.在此基础上,通过变量替换,将该模型转化为线性规划模型.由于线性规划模型不仅能够求得解析解,而且有现成的求解软件,因此不但便于问题求解,而且更加方便、可靠.最后进行了示例计算,验证了给出的马尔柯夫状态转移概率矩阵优化算法的可行性和正确性.     

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.     

LINEAR SEARCH FOR A BROWNIAN TARGET MOTION

A target is assumed to move according to a Brownian motion on the real line. The searcher starts from the origin and moves in the two directions from the starting point.The object is to detect the target. The purpose of this paper is to find the conditions under which the expected value of the first meeting time of the searcher and the target is finite,and to show the existence of a search plan which made this expected value minimum.     

Constrained Markov decision processes with first passage criteria

This paper deals with constrained Markov decision processes (MDPs) with first passage criteria. The objective is to maximize the expected reward obtained during a first passage time to some target set, and a constraint is imposed on the associated expected cost over this first passage time. The state space is denumerable, and the rewards/costs are possibly unbounded. In addition, the discount factor is state-action dependent and is allowed to be equal to one. We develop suitable conditions for the existence of a constrained optimal policy, which are generalizations of those for constrained MDPs with the standard discount criteria. Moreover, it is revealed that the constrained optimal policy randomizes between two stationary policies differing in at most one state. Finally, we use a controlled queueing system to illustrate our results, which exhibits some advantage of our optimality conditions.     

Medium range optimization of copper extraction planning under uncertainty in future copper prices

Deterministic mine planning models along a time horizon have proved to be very effective in supporting decisions on sequencing the extraction of material in copper mines. Some of these models have been developed for, and used successfully by CODELCO, the Chilean state copper company. In this paper, we wish to consider the uncertainty in a very volatile parameter of the problem, namely, the copper price along a given time horizon. We represent the uncertainty by a multistage scenario tree. The resulting stochastic model is then converted into a mixed 0–1 Deterministic Equivalent Model using a compact representation. We first introduce the stochastic model that maximizes the expected profit along the time horizon over all scenarios (i.e., as in a risk neutral environment). We then present several approaches for risk management in a risk averse environment. Specifically, we consider the maximization of the Value-at-Risk and several variants of the Conditional Value-at-Risk (one of them is new), the maximization of the expected profit minus the weighted probability of having an undesirable scenario in the solution provided by the model, and the maximization of the expected profit subject to stochastic dominance constraints recourse-integer for a set of profiles given by the pairs of target profits and bounds on either the probability of failure or the expected profit shortfall. We present an extensive computational experience on the actual problem, by comparing the risk neutral approach, the tested risk averse strategies and the performance of the traditional deterministic approach that uses the expected value of the uncertain parameters. The results clearly show the advantage of using the risk neutral strategy over the traditional deterministic approach, as well as the advantage of using any risk averse strategy over the risk neutral one.     

Nonlinear instability of half-solitons on star graphs

We consider a half-soliton stationary state of the nonlinear Schrödinger equation with the power nonlinearity on a star graph consisting of N edges and a single vertex. For the subcritical power nonlinearity, the half-soliton state is a degenerate critical point of the action functional under the mass constraint such that the second variation is nonnegative. By using normal forms, we prove that the degenerate critical point is a saddle point, for which the small perturbations to the half-soliton state grow slowly in time resulting in the nonlinear instability of the half-soliton state. The result holds for any $N\ge 3$ and arbitrary subcritical power nonlinearity. It gives a precise dynamical characterization of the previous result of Adami et al. (2012) [2], where the half-soliton state was shown to be a saddle point of the action functional under the mass constraint for $N=3$ and for cubic nonlinearity.     

A note on Fröberg's conjecture for forms of equal degrees

In this note we study ideals generated by generic forms in polynomial rings over any algebraicly closed field of characteristic zero. We prove for many cases that the $(d+k)$-th graded component of an ideal generated by generic forms of degree d has the expected dimension (given by dimension count). And as a consequence of our result, we obtain that ideals generated by several generic forms of degrees d usually have the expected Hilbert series. The precise form of this expected Hilbert series, in general, is known as Fröberg's conjecture.     

Risk minimising strategies for revenue management problems with target values

Consider a risk-averse decision maker in the setting of a single-leg dynamic revenue management problem with revenue controlled by limiting capacity for a fixed set of prices. Instead of focussing on maximising the expected revenue, the decision maker has the main objective of minimising the risk of failing to achieve a given target revenue. Interpreting the revenue management problem in the framework of finite Markov decision processes, we augment the state space of the risk-neutral problem definition and change the objective function to the probability of failing a certain specified target revenue. This enables us to obtain a dynamic programming solution that generates the policy minimising the risk of not attaining this target revenue. We compare this solution with recently proposed risk-sensitive policies in a numerical study and discuss advantages and limitations.