煤矿瓦斯爆炸事故单危险源风险度量模型研究

本文研究了煤矿瓦斯爆炸事故危险源的分类,把危险源划分为人的不安全行为、机器设备不安全状态、环境不安全特征和管理缺陷四大类,并根据煤矿现场调查各类危险源的数据以及相应数学方法的特点,提出煤矿瓦斯爆炸事故人、机器设备(物)、环境、管理四类危险源的风险度量方法,在此基础上构建四类危险源的风险度量模型。研究表明,危险源的风险度量模型由风险发生的可能性、危险源重要度以及事故导致的损失构成;危险源风险发生的可能性,在具体应用中可以采用各类危险源的不可靠度、故障率等来衡量;危险源在事故中的重要度可以通过分析事故故障树种要素结构重要性获取。根据风险评价的结果,可以对危险源进行分级排序,从而为煤矿事故单危险源的控制提供依据。     

Some remarks on the duality of continuous time markov chains

A simple proof of Siegmund's result on the relation between dual q-matrices and dual transition functions for Markov chains is given. A byproduct is a uniqueness result for minimal solutions of stochastically monotone q-matrices.     

A statistical measure of internal consistency

A test for homogeneity of several populations against the simple tree alternative is proposed when the observations in various groups are subject to the same pattern of random right-censorship. The test is a generalization of the one proposed by Slivka (1970) which is useful when testing time is expensive so that an early termination of an experiment is desirable. The power of the test is examined in a simulation study.     

Multivariate forests with missing mixed outcomes

In this article, we propose a multivariate random forest method for multiple responses of mixed types with missing responses. Imputation is performed for each bootstrap sample used to build the individual trees that form the forest. The individual trees are built using a weighted splitting rule allowing downweighting of imputed observations. A simulation study shows the benefits of this approach over complete case analysis when missing responses are missing completely at random and missing at random (MAR). In particular, the gain in prediction accuracy of the proposed method is larger in the MAR case and also increases as the proportion of missing increases.     

Conditional entropy,entropy density,and strong law of large numbers for generalized controlled tree-indexed Markov chains

In this paper, we first introduces a tree model without degree boundedness restriction namely generalized controlled tree T, which is an extension of some known tree models, such as homogeneous tree model, uniformly bounded degree tree model, controlled tree model, etc. Then some limit properties including strong law of large numbers for generalized controlled tree-indexed non homogeneous Markov chain are obtained. Finally, we establish some entropy density properties, monotonicity of conditional entropy, and entropy properties for generalized controlled tree-indexed Markov chains.     

Stochastic correlation coefficient ensembles for variable selection

In this paper, we propose a novel Max-Relevance and Min-Common-Redundancy criterion for variable selection in linear models. Considering that the ensemble approach for variable selection has been proven to be quite effective in linear regression models, we construct a variable selection ensemble (VSE) by combining the presented stochastic correlation coefficient algorithm with a stochastic stepwise algorithm. We conduct extensive experimental comparison of our algorithm and other methods using two simulation studies and four real-life data sets. The results confirm that the proposed VSE leads to promising improvement on variable selection and regression accuracy.     

Edge Estimation in the Population of a Binary Tree Using Node-Sampling

Suppose a finite population of several vertices, each connected to single or multiple edges. This constitutes a structure of graphical population of vertices and edges. As a special case, the graphical population like a binary tree having only two child vertices associated to parent vertex is taken into consideration. The entire binary tree is divided into two sub-graphs such as a group of left-nodes and a group of right-nodes. This paper takes into account a mixture of graph structured and population sampling theory together and presents a methodology for mean-edge-length estimation of left sub-graph using right edge sub-graph as an auxiliary source of information. A node-sampling procedure is developed for this purpose and a class of estimators is proposed containing several good estimators. Mathematical conditions for minimum bias and optimum mean squared error of the class are derived and theoretical results are numerically supported with a test of 99% confidence intervals. It is shown that suggested class has a sub-class of optimum estimators, and sample-based estimates are closer to the true value of the population parameter.     

凸连续泛函极小点的一个等价条件

本文利用允许方向锥讨论了凸连续函数在凸集上的极小点的充分必要条件，其主要结果是定理2。     

基于滑动窗口的自适应网页预测模型

PPM模型广泛应用于Web预取技术,但大多数的PPM模型不具有自适应性,不能反映用户浏览模式的改变。通过对标准PPM模型的扩展,提出基于滑动窗口的自适应网页预测模型。该模型仅保留处于滑动窗口之内的最近访问序列,从而反映用户兴趣的变化,同时利用非压缩后缀树增量式添加新的用户请求和删除过时的浏览信息,以提高更新速度。实验表明,该模型能更准确地描述用户在Web上的浏览特征,在预取性能上明显地优于以往的模型。     

肇庆市居住区绿化树种及其分析

通过对肇庆市居住区的实地调研与树种鉴定，记录了134种绿化树种，其中乔木75种。灌木53种，木质藤本6种。主要隶属于桑科、棕榈科、苏木科、大戟科、夹竹桃科、挑金娘科。经过分析，有针对性地对肇庆市居住区提出了绿化建议，建议多采用耐荫植物与景观植物，合理进行树种配置，可采用复式立体栽植及景观陪衬等绿化方式。