Influence diagrams for Bayesian decision analysis

Influence diagrams for representing Bayesian decision problems are redefined in a formal way using conditional independence. This makes the graphs somewhat more helpful for exploring the consequences of a clients state beliefs. Some important results about the manipulation of influence diagrams are extended and reviewed as is an algorithm for computing an optimal policy. Two new results about the manipulation of influence diagrams are derived. A novel influence diagram representing a practical decision problem is used to illustrate the methodologies presented in this paper.     

Sufficient Conditions for a Digraph to be Supereulerian

A (di)graph is supereulerian if it contains a spanning eulerian sub(di)graph. This property is a relaxation of hamiltonicity. Inspired by this analogy with hamiltonian cycles and by similar results in supereulerian graph theory, we analyze a number of sufficient Ore type conditions for a digraph to be supereulerian. Furthermore, we study the following conjecture due to Thomassé and the first author: if the arc‐connectivity of a digraph is not smaller than its independence number, then the digraph is supereulerian. As a support for this conjecture we prove it for digraphs that are semicomplete multipartite or quasitransitive and verify the analogous statement for undirected graphs.     

不同类型随机变量和差积商的分布

研究两种不同类型的随机变量,即离散型随机变量ζ与连续型随机变量η的和（ζ＋η）、差（ζ-η）、积（ζη）、商（ζ/η）的分布,给出这些分布的密度函数．     

向量组线性相关性的教学方法与技巧

向量组线性相关性是线性代数教学中的一项重要内容．由于概念比较抽象、定理难以理解,因此一直是线性代数教学环节中的一项难点．通过对向量组线性相关性的定义以及判断方法进行了形象的描述,建立向量组线性相关性与矩阵、线性方程组之间的关系,有利于学生理解向量组线性相关性的真正内涵与简便求解方法．     

Analytic smoothing effect for global solutions to nonlinear Schrödinger equations

We prove the global existence of analytic solutions to the Cauchy problem for the cubic Schrödinger equation in space dimension n?3 for sufficiently small data with exponential decay at infinity. Minimal regularity assumption regarding scaling invariance is imposed on the Cauchy data.     

Generation of analytic semigroups by generalized Ornstein-Uhlenbeck operators with potentials

It is shown that the generalized Ornstein-Uhlenbeck operator “with potential” AΦ,G,Vu:=Δu−∇Φ⋅∇u+G⋅∇u−Vu with suitable domain generates an analytic semigroup on the weighted space Lp(RN,μ), 1<p<∞, where . The result extends the generation theorem established by Metafune-Prüss-Rhandi-Schnaubelt when V≡0 to the case where V?0, while the proof is based on their useful theorem that a class of second order elliptic operators generates an analytic semigroup on the unweighted space Lp(RN).     

Epistemic irrelevance in credal nets: The case of imprecise Markov trees

We focus on credal nets, which are graphical models that generalise Bayesian nets to imprecise probability. We replace the notion of strong independence commonly used in credal nets with the weaker notion of epistemic irrelevance, which is arguably more suited for a behavioural theory of probability. Focusing on directed trees, we show how to combine the given local uncertainty models in the nodes of the graph into a global model, and we use this to construct and justify an exact message-passing algorithm that computes updated beliefs for a variable in the tree. The algorithm, which is linear in the number of nodes, is formulated entirely in terms of coherent lower previsions, and is shown to satisfy a number of rationality requirements. We supply examples of the algorithm’s operation, and report an application to on-line character recognition that illustrates the advantages of our approach for prediction. We comment on the perspectives, opened by the availability, for the first time, of a truly efficient algorithm based on epistemic irrelevance.     

Painlevé analysis and new analytic solutions for variable-coefficient Kadomtsev-Petviashvili equation with symbolic computation

The variable-coefficient Kadomtsev-Petviashvili (KP) equation is hereby under investigation. Painlevé analysis is given out, and an auto-Bäcklund transformation is presented via the truncated Painlevé expansion. Based on the auto-Bäcklund transformation, new analytic solutions are given, including the soliton-like and periodic solutions. It is also reduced to a (1+1)-dimensional partial differential equation via classical Lie group method and the Painlevé I equation by CK direct method.     

Exact and explicit solutions of Euler-Painlevé equations through generalized Cole-Hopf transformations

More general Euler-Painlevé equations are exactly linearized using generalized Cole-Hopf transform and are shown to admit exact solutions in terms of Kummer functions. The asymptotic behaviours of Euler-Painlevé equations are also derived.     

ACUTA: A novel method for eliciting additive value functions on the basis of holistic preference statements

In multiple criteria decision aiding, it is common to use methods that are capable of automatically extracting a decision or evaluation model from partial information provided by the decision maker about a preference structure. In general, there is more than one possible model, leading to an indetermination which is dealt with sometimes arbitrarily in existing methods. This paper aims at filling this theoretical gap: we present a novel method, based on the computation of the analytic center of a polyhedron, for the selection of additive value functions that are compatible with holistic assessments of preferences. We demonstrate the most important characteristics of this technique with an experimental and comparative study of several existing methods belonging to the UTA family.