Deletions in random binary search trees: A story of errors

The usual assumptions for the average case analysis of binary search trees (BSTs) are random insertions and random deletions. If a BST is built by n random insertions the expected number of key comparisons necessary to access a node is 2 ln n+O(1). This well-known result is already contained in the first papers on such ‘random’ BSTs. However, if random insertions are intermixed with random deletions the analysis of the resulting BST seems to become more intricate. At least this is the impression one gets from the related publications since 1962, and it is quite appropriate to speak of a story of errors in this context, as will be seen in the present survey paper, giving an overview on this story.     

2型糖尿病相关单核苷酸多态性c/t位点相似性分析

2型糖尿病（非胰岛素依赖型糖尿病）具有明显的家族遗传特点,但它的基因起源很大程度上并未得到深入了解。几种遗传因素共同影响提高了患2型糖尿病及相关代谢性疾病的风险性。通过对与2型糖尿病相关联的单核苷酸多态性位点（SNPs）做相似性分析来揭示2型糖尿病的基本机制,并作为标记来定位和识别与这一疾病相关的基因。     

Total System Performance Assessment for Waste Disposal Using a Logic Tree Approach

The Electric Power Research Institute (EPRI) has sponsored the development of a model to assess the long-term, overall performance of the candidate spent fuel and high-level radioactive waste (HLW) disposal facility at Yucca Mountain, Nevada. The model simulates the processes that lead to HLW container corrosion, HLW mobilization from the spent fuel, and transport by groundwater, and contaminated groundwater usage by future hypothetical individuals leading to radiation doses to those individuals. The model must incorporate a multitude of complex, coupled processes across a variety of technical disciplines. Furthermore, because of the very long time frames involved in the modeling effort (10⁴ years), the relative lack of directly applicable data, and many uncertainties and variabilities in those data, a probabilistic approach to model development was necessary. The developers of the model chose a logic tree approach to represent uncertainties in both conceptual models and model parameter values. The developers felt the logic tree approach was the most appropriate. This paper discusses the value and use of logic trees applied to assessing the uncertainties in HLW disposal, the components of the model, and a few of the results of that model. The paper concludes with a comparison of logic trees and Monte Carlo approaches.     

客户流失危机分析的决策树方法

叙述了客户流失的基本概念,分析客户流失危机产生的原因,指出了传统的客户流失危机分析方法存在的问题,在ID3算法的基础上,提出一种加权熵的概念,并对ID3算法进行改进,提出了一种基于决策树的客户流失危机分析方法,通过一个客户流失危机的分析实验对该模型进行了验证.实验结果表明该方法是可行的和有效的,为客户流失危机分析和预警提供了一种新的研究思路和分析方法.     

用PO法对星斗山珙桐群落的排序研究

用PO法对星斗山珙桐群落进行排序。结果显示：由于环境梯度的差异,珙桐群落内有两种基本群丛类型,它们在种类组成、结构、生态特征及外貌等方面存在差别。     

Block diagrams and splitting criteria for classification trees

Various aspects of the classification tree methodology of Breiman et al., (1984) are discussed. A method of displaying classification trees, called block diagrams, is developed. Block diagrams give a clear presentation of the classification, and are useful both to point out features of the particular data set under consideration and also to highlight deficiencies in the classification method being used. Various splitting criteria are discussed; the usual Gini-Simpson criterion presents difficulties when there is a relatively large number of classes and improved splitting criteria are obtained. One particular improvement is the introduction of adaptive anti-end-cut factors that take advantage of highly asymmetrical splits where appropriate. They use the number and mix of classes in the current node of the tree to identify whether or not it is likely to be advantageous to create a very small offspring node. A number of data sets are used as examples.     

受弹性时间段和价值波动双重影响的项目组合选择问题研究

许多现有的项目组合模型都认为项目集合可以在固定的计划期完成,但是在实际的项目执行过程中,决策者为了使得高收益的项目纳入项目集合中或者放弃风险高的项目来释放更多的资金,会选择对项目组合固定的计划期进行灵活性调整。同时,考虑到项目未来价值的不确定性,本文利用实物期权的二叉树模型给出了价值波动的公式,进而建立了同时受弹性时间段和价值波动影响的项目组合选择的新模型,对传统的计算项目价值的净现值法进行补充。通过GAMS/BARON对算例进行求解,验证了模型的合理性和有效性。结果表明：考虑弹性时间段和价值波动的影响会给更符合企业长期的发展战略,给企业带来更大的收益,该模型也为处理不确定情况下的项目组合问题提供了新思路和新方法。     

Exploring gillnet catch efficiency of sardines in the coastal waters of Sri Lanka by means of three statistical techniques: a comparison of linear and nonlinear modelling techniques

The present investigation was undertaken to study the gillnet catch efficiency of sardines in the coastal waters of Sri Lanka using commercial catch and effort data. Commercial catch and effort data of small mesh gillnet fishery were collected in five fisheries districts during the period May 1999–August 2002. Gillnet catch efficiency of sardines was investigated by developing catch rates predictive models using data on commercial fisheries and environmental variables. Three statistical techniques [multiple linear regression, generalized additive model and regression tree model (RTM)] were employed to predict the catch rates of trenched sardine Amblygaster sirm (key target species of small mesh gillnet fishery) and other sardines (Sardinella longiceps, S. gibbosa, S. albella and S. sindensis). The data collection programme was conducted for another six months and the models were tested on new data. RTMs were found to be the strongest in terms of reliability and accuracy of the predictions. The two operational characteristics used here for model formulation (i.e. depth of fishing and number of gillnet pieces used per fishing operation) were more useful as predictor variables than the environmental variables. The study revealed a rapid tendency of increasing the catch rates of A. sirm with increased sea depth up to around 32 m.     

改进的Prim算法在求解旅行商问题中的应用

旅行商问题是图论中一个典型的组合优化问题,它的问题描述与图论中最小生成树问题的描述具有很多相似之处,在一些情形下,可以用最小生成树形成的路径来获得旅行商问题的最短巡回路径。首先给出了最小生成树Prim算法,然后对其算法进行了改进,通过改进的Prim算法成功求解了旅行商问题。     

投资项目评估实物期权法

在项目投资中,不确定性对项目投资评价、决策起了决定性的作用。净现值法(NPV法)忽视了项目投资的不可逆性和投资决策的可递延性,因此往往低估了项目投资的真实价值。运用实物期权原理分析了不确定性对项目投资评价和决策的影响,通过二项树模型将影响定量化,并进一步对实际投资行为作出了解释。