匹配于进化种群的局部网络图度量

为了分析匹配于进化种群的贝叶斯网络结构 ,给出了用于刻画局部贝叶斯网络度量的有关表示。依据贝叶斯狄利克雷度量 ,对于贝叶斯网络图中的 3个顶点 (对应于染色体的某 3个基因位置 ) ,研究了 3个顶点无连接、其中只有两个顶点存在有向连接、及 3个顶点存在两条有向边时的度量值关系。揭示了局部贝叶斯网络结构的固有特性 ,为进一步研究进化算法的种群结构提供了一条可行的途径。     

贝叶斯决策的影响图分析方法

对一般的贝叶斯决策问题, 常用的求解手段是决策树分析方法。本文则用影响图分析方法对贝叶斯决策问题进行表征和求解, 并将两个方法作了比较。另外, 本文给出了关于影响图变换运算的两个新结果。     

热力学准静态过程的教学研究

文章对热力学准静态过程与非静态过程进行教学研究,并提出处理热力学过程有效和准确的方法。     

To combine or not to combine? issues of combining forecasts

This paper addresses issues such as: Does it always pay to combine individual forecasts of a variable? Should one combine an unbiased forecast with one that is heavily biased? Should one use optimal weights as suggested by Bates and Granger over twenty years ago? A simple model which accounts for the main features of individual forecasts is put forward. Bayesian analysis of the model using noninformative and informative prior probability densities is provided which extends and generalizes results obtained by Winkler (1981) and compared with non-Bayesian methods of combining forecasts relying explicitly on a statistical model for the individual forecasts. It is shown that in some instances it is sensible to use a simple average of individual forecasts instead of using Bates and Granger type weights. Finally, model uncertainty is considered and the issue of combining different models for individual forecasts is addressed.     

应用免疫算法求解博弈问题

设计了用于求解博弈问题的免疫算法的结构,讨论了二进制编码情况下的多样性控制,探讨了利用免疫算法求解博弈问题的方法和优势,分析了博弈问题的适应度评估方案,证实了设计的免疫算法具有稳定的收敛性.并通过对几个完全信息静态博弈实例的计算,验证了免疫算法求解博弈问题的有效性.     

A bayesian approach to modelling stochastic cycles

This article deals with a fully Bayesian approach to describe the cyclical behaviour of a univariate time series. A damped sine wave where both the period and the damping factor are time varying is assumed as the underlying mathematical model for the cyclical component. The model is applied to two real data sets; the annual rainfall observations in Fortaleza, Brazil, and the annual Wolf sunspot numbers.     

利用先验信息修正经典限的可靠性评估方法

讨论可靠性评估中利用先验信息的问题 .在参数先验分布容易确定的场合 ,可利用先验信息对参数的经典估计进行修正 (即给出 Bayes估计 ) ,再基于该估计用经典的 WCF方法给出系统可靠度的置信下限 .该方法具有很好的精度 ,并克服了纯 Bayes方法受先验偏差影响较大的缺点 .文章对上述进行了补充 ,讨论了指数定时截尾数据情形下利用先验信息的可靠性评定问题 .给出了一种融合先验信息和试验数据的参数估计 ,该估计的特点是具有独立和的形式 ,基于该估计用 WCF法比基于通常的 Bayes估计简单 .另外 ,对参数先验分布难以确定的多参数寿命分布模型 (如 Weibull分布 ,本文在仅知其可靠度先验分布或可靠度先验一阶、二阶矩及可靠度的某先验分位点的条件下 (事实上工程专家较易给出上述可靠度的有关先验信息 ) ,将 Bayes,Fiducial及经典统计方法相结合 ,用可靠度的先验信息直接对可靠度的经典限作修正以获得融合了先验信息及试验数据的置信下限 ,模拟表明该种处理具有很好的精度 ,适合工程应用.     

带行动次序的博弈模型及其在经济学中的应用

参考前人的文献，从信息和行动次序的角度出发，建立了具有严格数学表达的博弈论模型，并在新的框架下讨论企业间相互竞争与合作的问题．     

Averaging over decision trees

Pruning a decision tree is considered by some researchers to be the most important part of tree building in noisy domains. While there are many approaches to pruning, the alternative of averaging over decision trees has not received as much attention. The basic idea of tree averaging is to produce a weighted sum of decisions. We consider the set of trees used for the averaging process, and how weights should be assigned to each tree in this set. We define the concept of afanned set for a tree, and examine how the Minimum Message Length paradigm of learning may be used to average over decision trees. We perform an empirical evaluation of two averaging approaches, and a Minimum Message Length approach.This work has been carried out with the support of the Defence Research Agency, Malvern.