印刷业中制版废液的回收与再利用

本文对凸版印刷废液的再利用以及添加剂和锌的回收进行了讨论。提出并解决了因表面活性剂，锌离子对酸腐液的影响而导致酸腐液性质变化的问题，并对废液中酸的再利用及添加剂和锌的回收提供了可行的方法。     

关于可加算子的有界、强有界与连续性研究

研究了拓扑线性空间中可加算子的有界、强有界以及连续之间的关系，将线性算子的相关结论推广到了可加算子上，并得到了赋拟、准范空间的相应结论．     

具有高簇系数的权重演化无标度网络模型

提出了一个演化的权重无标度网络模型.在传统的加权网络模型的强度优先连接机制基础上,考虑了网络按照模块结构和三角结构进行演化的特性.研究了模块结构和三角结构的演化机制对无标度模型结构特性的影响.仿真结果表明该权重网络的度、强度和权值都服从幂率分布,网络的平均强度与度之间具有高相关特性,网络的平均簇系数与度的函数关系服从幂率分布,模块结构和三角结构的演化机制能够显著提高网络的簇系数.     

An Application of Grey Clustering Method in the Sporting Clothing Style Evaluation

1. INTroDUCTIONIn recent years, sporting clothing is develOPed quickly all over the world. In order to upgrade the level of qualityand weaxing property of sporting clothing, it is necessary to reseaxch the style of sporting clothing, optimize thetechniques of production. In the past, the inspection of sporting clothing Style is a manual work through visionand feeling, but it is not scientific and has compaxative fall. Now some clothing style testing instrumellts havebeen introduced for th…     

点簇聚合的目标顶点的优化

研究了点簇聚合的目标顶点位置的计算问题。当计算过程中得到的目标顶点不在小单元之内,或者虽然在小单元之内,但目标顶点的位置不能唯一确定时,则将求解目标顶点的问题转化为求解带约束的二次优化问题。此二次优化问题的解既能保证目标顶点位于小单元之内,在位置上又最接近该点簇的重心。实验结果表明,该算法的时间效率类似于Lindstrom的算法,但在简化质量上要优于后者。     

A sequential fitting procedure for linear data analysis models

A particular factor analysis model with parameter constraints is generalized to include classification problems definable within a framework of fitting linear models. The sequential fitting (SEFIT) approach of principal component analysis is extended to include several nonstandard data analysis and classification tasks. SEFIT methods attempt to explain the variability in the initial data (commonly defined by a sum of squares) through an additive decomposition attributable to the various terms in the model. New methods are developed for both traditional and fuzzy clustering that have useful theoretic and computational properties (principal cluster analysis, additive clustering, and so on). Connections to several known classification strategies are also stated.The author is grateful to P. Arabie and L. J. Hubert for editorial assistance and reviewing going well beyond traditional levels.     

中国证券投资基金风格分类研究

差异化战略以及特定资产类别的超额收益促使投资基金在募集时就约定投资风格，但投资基金有可能在实际的运作过程中违背事先约定的投资风格．据此，在投资风格分类中引入了聚类分析方法，并同时采用晨星风格箱方法和聚类分析方法对中国证券投资基金的风格进行了分析．结果表明，大多数基金违背了募集说明书中约定的风格．     

基于自适应性神经网络和历史聚类的旅游规划

研究了不同类型的服务之间的关系,提出了一种基于使用历史的分层聚类,以提取有意义的使用模式,建立了智能旅游规划的自适应型神经网络结构.     

数据挖掘技术在团体医疗保险中的应用

将数据挖掘中的决策树技术应用于团体医疗保险理赔数据库中，提出了基于Clementine数据挖掘平台的理赔风险解决方案，为保险公司团体医疗保险理赔风险规则的提取和费率厘定提供决策依据，以提高团体医疗保险管理的科学性．     

A permutation-based algorithm for block clustering

Hartigan (1972) discusses the direct clustering of a matrix of data into homogeneous blocks. He introduces a stepwise divisive method for block clustering within a certain class of block structures which induce clustering trees for both row and column margins. While this class of structures is appealing, the stopping criterion for his method, which is based on asymptotic theory and the assumption that the individual elements of the data matrix are normally distributed, is quite restrictive. In this paper we propose a permutation-based algorithm for block clustering within the same class of block structures. By using permutation arguments to decide where to split and when to stop, our algorithm becomes applicable in a wide variety of cases, including matrices of categorical data and matrices of small-to-moderate size. In addition, our algorithm offers considerable flexibility in how block homogeneity is defined. The algorithm is studied in a series of simulation experiments on matrices of known structure, and illustrated in examples drawn from the fields of taxonomy, political science, and data architecture.