The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.     

整合资源调整职能促进发展--关于陕煤技校改革发展的思考

经过60年的发展,陕西煤炭技工院校形成了以服务煤业为特色的专业结构和办学模式,为祖国煤炭发展做出了不可替代的贡献。近年来,由于煤炭市场遇冷,行业技校吸引力持续减弱,如何走出困境,重铸辉煌,作者从整合职教资源,调整管理职能,转换办学模式的角度进行了分析思考,或许能给陕煤技校改革发展提供一些有益参考。     

基于LS-SVM逆系统的无轴承异步电机解耦控制

无轴承异步电机具有非线性、多变量和强耦合的特点,要实现电机稳定悬浮和旋转运行,必须对其进行非线性动态解耦控制。为了克服逆系统方法精确建模难的局限性,采用基于最小二乘支持向量机(LS-SVM)α阶逆系统方法对无轴承异步电机进行动态解耦控制的研究。首先利用最小二乘支持向量机辨识出无轴承异步电机的逆模型,然后将它串联在原系统前,将无轴承异步电机解耦成四个独立的伪线性子系统-2个径向位移子系统、一个速度子系统和一个磁链子系统。为保证鲁棒性能,最后对解耦后的系统采用非线性内模控制策略。研究表明,LS-SVMα阶逆系统方法能够实现无轴承异步电机径向悬浮力和旋转力之间的动态解耦控制,控制系统具有良好的静态和动态性能。     

基于 Siebel CRM 的电信业务的设计与实现*

随着企业的发展、信息技术的进步,以“客户为中心”的口号成为众多企业的经营理念;客户就是市场,逐渐成为企业竞争的唯一导向。针对传统客户关系管理系统的不足,利用Siebel系统在CRM 中的优势,设计出电信业的客户关系管理系统（CRM ）;利用Siebel CRM系统对其它系统的强大的支撑,实现电信业的系统集成,完全实现电信业的自动化经营;最终实现电信业的“以客户为中心”的理念,达到电信业存量经营的目标。     

企业各软件的数据共享和整合分析浅谈

本文主要根据大多数企业存在各种软件各自独立运行,各软件之间数据不能相互共享,一些旧软件或不适用的软件与目前主流操作系统不兼容等问题,分析问题并用接口和整合方法解决,此平台利用云计算技术,解决大多数企业建设信息平台投资大的问题,同时方便企业使用和维护.     

Continual conversion of free fatty acid in rice bran oil to triacylglycerol by immobilized lipase

Rice bran oil containing 30–50% free fatty acid was continually converted to an oil containing more than 75% of triacylglycerol (TG) by means of immobilized lipase. The reaction was carried out at 60°C for 24 h with dehydration and reactant mixing by dry nitrogen flow under a positive nitrogen atmosphere. Enzymatic TG synthesis with evaporation by heating was not suitable because of the increasing peroxide value of the oil. Part of this article was presented at the annual meeting of the Japan Oil Chemists' Society at Sendai, Japan, October, 16, 1990.     

TESTS FOR FRACTIONAL INTEGRATION:A MONTE CARLO INVESTIGATION

Abstract. The performance of the Geweke-Porter-Hudak (GPH) test, the modified rescaled range (MRR) test and two Lagrange multiplier (LM) type tests for fractional integration in small samples is examined using Monte Carlo methods. Both the GPH and MRR tests are found to be robust to moderate autoregressive moving-average components, autoregressive conditional heteroskedasticity effects and shifts in the variance. However, these two tests are sensitive to large autoregressive moving-average components and shifts in the mean. It is also found that the LM tests are sensitive to deviations from the null hypothesis. As an illustration, the GPH test is applied to two economic data series.     

试论计算机应用技术与信息管理的整合

当今时代是一个以信息为核心发展的时代,计算机应用技术和信息管理的整合是科技发展过程中的一个重要内容。随着新型信息时代的到来,无论什么行业,都会或多或少的涉及到信息的管理技术。利用计算机方便、高速、准确等特点,把计算机和信息管理技术有效的结合起来,是保证各行各业工作质量、提高工作效率、使各项工作能够顺利开展的必备条件,因为计算机应用技术能够综合管理信息,为各有关部门提供更为科学完整的信息资料,创建快速健全的管理平台,从而提高管理的水平,促进行业的发展。     

信息技术在数学教学中的应用研究

以多媒体计算机和网络为核心的信息技术在小学数学教学中的运用,使数学教学活动更加丰富多彩,激发学生的学习兴趣,增强学生的主体意识,培养学生的技能,拓展学生探究的时间和空间,引发学生主动、积极、创新的思维,开发学生的智力,促进学生主动学习,主动发展,从而有效地提高课堂教学效率.