多学科协同设计模型感知研究*

为了解决多学科异构系统中产品设计模型之间设计修改的感知问题, 针对设计模型和分析模型提出由模型寻找到协同适应的模型感知应用方法,阐述了各学科之间协同感知过程、感知之后映射关系更新和分析模型修改的实现流程,将传统的人与人感知模式转变为模型到模型感知模式。通过分析模型修改方法实现设计模型到分析模型的感知处理,重新处理分析模型。最后通过感知表达方法实现分析模型到设计模型的感知表达,将分析结果可视化反映到设计模型上。     

无线网络中TCP/NC协议性能分析与仿真验证

为改进传统传输控制协议( TCP)在无线网络中的性能,运用Matlab对TCP Reno,TCP Vegas和基于网络编码的TCP/NC吞吐率分析模型进行数值求解,分析3个模型在不同网络环境下应达到的理论值,验证TCP/NC模型在理论上能否提高其吞吐率。基于NS-2对3种吞吐率模型进行仿真,结果表明,TCP/NC及其分析模型可有效改进TCP协议。     

基于句法树的藏语最长名词短语识别

最长名词短语携带着丰富的句法和语义信息,经常与句法成分对应,在句子中充当一定的语义角色。最长名词短语识别在自然语言处理中占重要地位,是分析和理解句子结构、意义的基础。该文通过梳理不同概念的最长名词短语的含义,从句法树角度界定了藏语最长名词短语的基本概念;从句法树库中抽取6 038个句子,分析了最长名词短语的结构类型、边界特征和出现频次,最后采用序列标注模型和句法分析模型对最长名词短语进行识别。序列标注模型识别结果的正确率、召回率和F₁值分别为87.14%、84.72%、85.92%。句法分析模型识别结果的正确率、召回率、F₁值分别为85.02%、84.51%、84.76%。     

支持界面自动生成的模型研究

为支持界面工程化设计,提出一种基于模型驱动思想的支持界面自动生成的ADS模型。ADS模型由分析模型、会话模型和显示模型构成。分析模型完成对界面功能和数据信息的建模,依据给定的转换规则,由会话模型生成界面的抽象视图,通过显示模型处理抽象视图的可视化和布局问题,并用UsiXML界面描述语言加以描述,组合UsiXML片段成XML文件,由框架解析XML文件生成用户界面。     

职业教育大数据分析模型构建方法的研究与应用

随着智慧教育建设和职业教育数据海量化,大数据分析成为有效利用数据的重要途径。大数据分析模型构建方法是大数据分析的关键。笔者结合大数据技术与教育内外部指标体系,提出了职业教育大数据分析模型构建方法,探讨了大数据分析业务流程,构建了以指标体系模型、数据分析模型和数据展现模型为基础的职业教育外部与内部大数据分析模型,并通过第三方BI分析开源工具对模型及构建方法进行应用实践。研究结果表明,职业教育大数据分析模型构建方法具有一定可行性,以期此方法为职业教育大数据分析应用建设提供借鉴。     

分布式异构地理分析模型共享门户的初步研究

针对目前GIS模型分析功能不足的困境,提出分布式异构地理分析模型共享门户的研究思路;基于地球系统科学理论,设计模型资源的分类组织体系,研究模型资源的表达形式和封装方法,突出语义和数据功能上的标准化;设计地理分析模型共享服务框架,以此克服分布式环境所引起的模型资源的访问障碍;构建了分布式环境下异构地理分析模型共享门户,并探讨该共享门户所具有的功能体系。     

遥感影象统计分析及其扩展模型

首先对遥感影象统计分析方法模型进行了回顾和综述,并分析了传统统计分析模型存在的缺陷,然后分别从传统的地学分析方法、神经计算模型、进化计算模型、稳健统计理论等几个不同的角度,提出了遥感数理统计分析模型扩展的方向,并通过几个具体模型对遥感统计分析扩展模型进行了初步探讨。     

基于RUP的科技基础数据库系统的设计

针对基于RUP/UML的数据库系统分析方法进行研究:在基于面向对象UML的平台上,以科技基础数据库系统为研究对象,对其用例模型、分析模型、设计模型和实现模型进行了分析设计,并采用UML建模工具Rational ROSE进行进一步的辅助分析与设计,得到了本系统的相关实现模型。文中的研究对数据库系统的分析设计提供了一种实用的技术途径。     

基于优先级队列的SIP DoS洪泛攻击防御模型

研究了NGN中的DoS攻击防御机制,利用排队论方法搭建出SIP DoS攻击M/M/1/K队列分析模型,设计出一种SIPDoS攻击防御模型.该模型将优先级队列引入到SIP服务器的消息处理中,从而减轻INVITE洪泛攻击对服务器的影响.最后通过NS2仿真工具对防御模型的性能进行了仿真分析,仿真结果表明,基于优先级队列的SIPDoS洪泛攻击模型能够有效地降低系统的响应时间.     

自然语言处理中的模型

本文简单介绍了自然语言处理发展的现状,讨论了自然语言处理模型,将其分为三大类：分析模型、统计模型及混合模型。具体介绍了分析模型原理及存在的问题,重点讨论了各种统计模型的特点及局限性,最后简单介绍了混合模型,并指出目前自然语言处理技术中存在的问题。     

Quantitative credit risk assessment using support vector machines: Broad versus Narrow default definitions

This paper compares support vector machine (SVM) based credit-scoring models built using Broad (less than 90 days past due) and Narrow (greater than 90 days past due) default definitions. When contrasting these two types of models, it was shown that models built using a Broad definition of default can outperform models developed using a Narrow default definition. In addition, this paper sought to create accurate credit-scoring models for a Barbados based credit union. Here, the results of empirical testing reveal that credit risk evaluation at the Barbados based institution can be improved if quantitative credit risk models are used as opposed to the current judgmental approach.     

Consideration of purchase dependence in inventory management

This paper emphasizes the importance of identifying and considering ‘purchase dependence,’ which is when the purchase of an item is dependent on the availability of the other items demanded in the same order. Even though purchase dependence is an important factor in designing an inventory replenishment policy, it has remained mostly unaddressed. Purchase dependence is different to demand dependence. Purchase dependence deals with the purchase behavior of customers, whereas demand dependence deals with the correlation among demands. This paper is the first to develop inventory models for purchase-dependent inventory systems. Through simulation experiments, this paper demonstrates that the developed inventory models, which include purchase dependence, incur less inventory operations costs (and satisfy more service level constraints) than other inventory models.     

Modelling the credit risk for portfolios of consumer loans: Analogies with corporate loan models

The New Basel accord has highlighted the need for models of the credit risk in portfolios of consumer loans. There are really no such models of the risks in consumer loan portfolios even though there is a well established industry – credit scoring – in modelling the risk of individual loans. Yet there are a number of models of the credit risk of portfolios of corporate loans. This paper discusses if and how one could use equivalent approaches to building such models in consumer lending even if the models themselves cannot translate across because of the assumptions underlying them.     

尺寸公差模型

尺寸公差模型对产品信息的完备性和尺寸驱设计都是极为重要的。常见的尺寸公差模型是对传统工程图尺寸标注的实现，缺少设计过程方面的理论支持。文章还提出了特的特征的尺寸模式生约束模式的概念，给出了实例并讨论其应用。     

Performance evaluation of hybrid Wavelet-ANN and Wavelet-ANFIS models for estimating evapotranspiration in arid regions of India

This paper evaluates the ability of wavelet transform in improving the accuracy of artificial neural network (ANN) and adaptive neuro-fuzzy interface systems (ANFIS) models. In this study, the performance of hybrid Wavelet-ANN and Wavelet-ANFIS models for estimating daily evapotranspiration in arid regions was evaluated. Prior to the development of models, gamma test was used to identify the best input combinations that could be used under limited data scenario. Performance of the proposed hybrid models was compared to ANN, ANFIS, and conventionally used Hargreaves equation. The results revealed that use of wavelet transform as data preprocessing technique enhanced the efficiency of ANN and ANFIS models. Wavelet-ANN and Wavelet-ANFIS performed reasonably better than other models. Better handling of wavelet-decomposed input variables enabled Wavelet-ANN models to perform slightly better than the Wavelet-ANFIS models. W-ANN2 (RMSE = 0.632 mm/day and R = 0.96) was found to be the best model for estimating daily evapotranspiration in arid regions. The proposed W-ANN2 model used second-level db3 wavelet-decomposed subseries of temperature and previous day evapotranspiration values as inputs. The study concludes that hybrid Wavelet-ANN and Wavelet-ANFIS models can be effectively used for modeling evapotranspiration.

     

Using the Model Coupling Toolkit to couple earth system models

Continued advances in computational resources are providing the opportunity to operate more sophisticated numerical models. Additionally, there is an increasing demand for multidisciplinary studies that include interactions between different physical processes. Therefore there is a strong desire to develop coupled modeling systems that utilize existing models and allow efficient data exchange and model control. The basic system would entail model “1” running on “M” processors and model “2” running on “N” processors, with efficient exchange of model fields at predetermined synchronization intervals. Here we demonstrate two coupled systems: the coupling of the ocean circulation model Regional Ocean Modeling System (ROMS) to the surface wave model Simulating WAves Nearshore (SWAN), and the coupling of ROMS to the atmospheric model Coupled Ocean Atmosphere Prediction System (COAMPS). Both coupled systems use the Model Coupling Toolkit (MCT) as a mechanism for operation control and inter-model distributed memory transfer of model variables. In this paper we describe requirements and other options for model coupling, explain the MCT library, ROMS, SWAN and COAMPS models, methods for grid decomposition and sparse matrix interpolation, and provide an example from each coupled system. Methods presented in this paper are clearly applicable for coupling of other types of models.     

Comparison procedure of predicting the time to default in behavioural scoring

The paper deals with the problem of predicting the time to default in credit behavioural scoring. This area opens a possibility of including a dynamic component in behavioural scoring modelling which enables making decisions related to limit, collection and recovery strategies, retention and attrition, as well as providing an insight into the profitability, pricing or term structure of the loan. In this paper, we compare survival analysis and neural networks in terms of modelling and results. The neural network architecture is designed such that its output is comparable to the survival analysis output. Six neural network models were created, one for each period of default. A radial basis neural network algorithm was used to test all six models. The survival model used a Cox modelling procedure. Further, different performance measures of all models were discussed since even in highly accurate scoring models, misclassification patterns appear. A systematic comparison ‘3 + 2 + 2’ procedure is suggested to find the most effective model for a bank. Additionally, the survival analysis model is compared to neural network models according to the relative importance of different variables in predicting the time to default. Although different models can have very similar performance measures they may consist of different variables. The dataset used for the research was collected from a Croatian bank and credit customers were observed during a 12-month period. The paper emphasizes the importance of conducting a detailed comparison procedure while selecting the best model that satisfies the users’ interest.     

实时CORBA系统调度模型的分析和比较

分析了TAO系统和NraD／URI系统的调度模型以及分别由Bettati＆Sun和东南大学提出的端到端调度模型的模型描述和调度方式。在调度模型的描述能力、计算能力、适用范围和存在的联系等方面对上述调度模型进行了分析和比较。     

Improving Fault Detection in Modified Code ——- A Study from the Telecommunication Industry

Many software systems are developed in a number of consecutive releases. In each release not only new code is added but also existing code is often modified. In this study we show that the modified code can be an important source of faults. Faults are widely recognized as one of the major cost drivers in software projects. Therefore, we look for methods that improve the fault detection in the modified code. We propose and evaluate a number of prediction models that increase the efficiency of fault detection. To build and evaluate our models we use data collected from two large telecommunication systems produced by Ericsson. We evaluate the performance of our models by applying them both to a different release of the system than the one they are built on and to a different system. The performance of our models is compared to the performance of the theoretical best model, a simple model based on size, as well as to analyzing the code in a random order （not using any model）. We find that the use of our models provides a significant improvement over not using any model at all and over using a simple model based on the class size. The gain offered by our models corresponds to 38-57% of the theoretical maximum gain.