基于决策树的可复用软件的研究及应用

在基于可复用构件库的软件开发中,如何从构件库中查询满足条件的构件是构件库系 统的研究重点之一。数据挖掘技术为解决上述问题提供了一条可行的途径,本文是在构件库系 统及用户反馈信息数据库的基础上,利用决策树分类器,得出一些实用的构件复用规则,从而为 复用者理解和选取构件提供了一定程度的辅助决策支持,为复用的成功提供了技术保障。     

对角型拟线性双曲方程组周期解的Blowup

本文考虑具周期初始数据的对角型拟线性双曲方程组Cauchy问题 ,证明其经典周期解一定在有限时间内破裂 ,且给出了经典解生命跨度上界估计 .     

世界朽木甲分类研究进展与我国种类名录

朽木甲是一个经济意义较为重要的昆虫类群,曾被作为一个独立科使用了近200年,于20世纪90年代被作为拟步甲科的亚科单位.本文对世界朽木甲分类研究的基本历史与现状、分类文献、分类系统和种类情况做了较详细介绍,并依据已知种类进行了区系分析,首次列出中国2族、16属、146种的系统目录.     

《科图法》中医药类目下的中医现代研究子类(62.03)探索

结合实际工作,就《科图法》第3版医卫类中的中医、中药类目下的中医现代研究子类进行品评、疏理、发掘,以期更好地利用类目资源服务于标引工作。     

绢云母石英片岩公路隧道围岩分级研究

在隧道建设过程中,准确的围岩分级对保证隧道施工的稳定性有重要意义。通过对典型绢云母石英片岩隧道岩石样本进行分析,得出与之相适应的BQ优化公式。针对绢云母石英片岩的特性,对BQ分级法中地下水修正系数进行重新考虑;并引入黏土矿物含量的修正指标和软弱夹层的修正指标,对BQ法进行修正,得出修正以后的建议[BQ]'值法公式。以在建十房高速通省隧道为例,进行验证分析,得出[BQ]'分级法确定的围岩级别与实际开挖揭露围岩级别较相符的结论,可为类似隧道围岩分级提供参考。     

Comparison of classifications using measures intermediate between metric dissimilarity and consensus similarity

Two fundamental approaches to the comparison of classifications (e g, partitions on the same finite set of objects) can be distinguished One approach is based upon measures of metric dissimilarity while the other is based upon measures of similarity, or consensus These approaches are not necessarily simple complements of each other Instead, each captures different, limited views of comparison of two classifications The properties of these measures are clarified by their relationships to Day's complexity models and to association measures of numerical taxonomy The two approaches to comparison are equated with the use of separation and minimum value sensitive measures, suggesting the potential application of an intermediate sensitive measure to the problem of comparison of classifications Such a measure is a linear combination of separation sensitive and minimum value sensitive components The application of these intermediate measures is contrasted with the two extremes The intermediate measure for the comparison of classifications is applied to a problem of character weighting arising in the analysis of Australian stream basinsWe thank Bill Day, Mike Austin, Peter Minchin and two anonymous referees for many helpful comments We also thank P Arabie for useful discussion of consensus methods and character weighting     

企业经营失败评价方法研究进展述评

20世纪80年代末期，学者们开始尝试使用新的方法替代传统的横截面统计方法来研究企业经营失败的评价问题，并体现出一定的优越性。本文选取基于模糊法则的分类模型、粗糙集分析、混沌模型、自组织映射、生存分析、累积总和模型、固定效应的面板数据logit模型、多维标度八种较为典型的新方法进行重点评述，分析各个方法的优势与局限性，进而阐述新方法的特点及其在研究中存在的不足，并对未来的研究方向进行展望。     

Robust classification procedures based on dichotomous and continuous variables

For classifying a univariate or a multivariate observation in one of the two populations, Tiku and Balakrishnan (1984) and Balakrishnan, Tiku and Shaarawi (1985) developed robust (to departures from normality) procedures. These procedures are extended here to situations where the classification has to be based on the observed value of a pair of variables, one being a dichotomous random variable and the other a univariate or a multivariate continuous random variable.We are very grateful to the referees for their comments which led to a substantial improvement of an earlier draft of this paper. Thanks are also due to the Natural Sciences and Engineering Council of Canada for a research grant to M.L. Tiku.     

An Authentication Technique Based on Classification

We present a novel watermarking approach based on classification for authentication,in which a watermark is embedded into the host image.When the marked image is modified,the extracted watermark is also different to the original watermark,and different kinds of modification lead to different extracted watermarks,In this paper,different kinds of modification are considered sa classes,and we used classification algorithm to recognize the modifications with high probability.Simulation results show that the proposed method is potential and effective.     

Clustering criteria for discrete data and latent class models

We show that a well-known clustering criterion for discrete data, the information criterion, is closely related to the classification maximum likelihood criterion for the latent class model. This relation can be derived from the Bryant-Windham construction. Emphasis is placed on binary clustering criteria which are analyzed under the maximum likelihood approach for different multivariate Bernoulli mixtures. This alternative form of criterion reveals non-apparent aspects of clustering techniques. All the criteria discussed can be optimized with the alternating optimization algorithm. Some illustrative applications are included.

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Résumé Nous montrons que le critère de classification de l'information, souvent utilisé pour les données discrètes, est très lié au critère du maximum de vraisemblance classifiante appliqué au modèle des classes latentes. Ce lien peut être analysé sous l'approche de la paramétrisation de Bryant-Windham. L'accent est mis sur le cas des données binaires qui sont analysées sous l'approche du maximum de vraisemblance pour les mélanges de distributions multivariées de Bernoulli. Cette forme de critère permet de mettre en évidence des aspects cachés des méthodes de classification de données binaires. Tous les critères envisagés ici peuvent être optimisés avec l'algorithme d'optimisation alternée. Des exemples concluent cet article.