基于范例库推理的软件成本估算模型研究

用传统的经验函数估算软件成本有很多局限性，采用基于范例库推理的估算方法可以很好地弥补其中的问题。讨论了软件成本估算和基于CBR推理研究的特点，从总体上阐述了COSCBR系统结构，描述了系统重要的研究方面：影响软件成本因素；层次推理；COSCRB系统的范例表示方法；相似度的基本计算算法。     

Hydraulic Circuit Design and Dynamic Learning Using Case-based Reasoning

This paper describes the design and implementation of a hydraulic circuit design system using case-based reasoning (CBR) paradigm from AI community The domain of hydraulic circuit design and case-based reasoning are briefly reviewed Then a proposed methodology in compuer-aided circuit design and dynamic leaning with the use of CBR is described Finally an application example is selected to illustrate the ussfulness of applying CBR in hydraulic circuit design with leaming.     

基于案例的维修性智能设计技术研究

产品维修性的设计长期以来依赖于积累的经验。文章在大量收集维修性设计技术案例的基础上,有针对性的制作多媒体信息材料。提出了基于实例的智能设计技术并实现了计算机辅助工程系统,详细阐明了该系统的组成、结构、功能,以及所采用的基于案例的推理技术、数据采掘技术。     

案例推理属性权重的分配模型比较研究

案例推理系统中各属性权重的赋值决定了案例之间的相似度 大小,进而对推理结果的正确与否产生显著影响.以属性加权K-最近邻 相似案例检索为基础,讨论了使用注水原理分配属性权重的机理,并通过建 立权重分配的合理性指标,构造拉格朗日函数对权重进行优 化求解,得到了收敛的注水分配算法.通过五折交叉的模式分类实验 ,分别对属性权重的平均分配法、注水分配算法和遗传算法分配法进行了比较研究,案例推理分类结果证明,在引入注水分配算法后,其分类性能得到有效改善.     

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.     

用神经网络来实现基于范例的推理系统

范例推理与神经网络有一种自然的联系，神经网络有许多优点，利用神经网络来实现范例推理可以取得非常好的效果。文章首先详细探讨了在范你推理中使用的神经网络模型与技术，并给出了其上的搜索与学习算法以及数据挖掘算法，旨在提高范例推理系统的鲁棒性和知识获取的自动化程度。     

一种改进的案例推理分类方法研究

特征属性的权重分配和案例检索策略对案例推理（Case-based reasoning,CBR）分类的准确率有显著影响. 本文提出一种结合遗传算法、内省学习和群决策思想改进的CBR分类方法. 首先,利用遗传算法得到多组属性权重,再根据内省学习原理对每组权重进行迭代调整;然后,通过案例群检索策略得到满足大多数原则的群决策分类结果;最后,以典型分类数据集的对比实验证明了本文方法能进一步提高CBR分类的准确率. 这表明内省学习可以保证权重分配的合理性,案例群检索策略能充分利用案例库的潜在信息,对提升CBR的学习能力有显著作用.     

Case-based retrieval of 3-dimensional shapes for the design of metal castings

This paper describes research into retrieval based on 3-dimensional shapes for use in the metal casting industry. The purpose of the system is to advise a casting engineer on the design aspects of a new casting by reference to similar castings which have been prototyped and tested in the past. The key aspects of the system are the orientation of the shape within the mould, the positions of feeders and chills, and particular advice concerning special problems and solutions, and possible redesign. The main focus of this research is the effectiveness of similarity measures based on 3-dimensional shapes. The approach adopted here is to construct similarity measures based on a graphical representation deriving from a shape decomposition used extensively by experienced casting design engineers. The paper explains the graphical representation and discusses similarity measures based on it. Performance measures for the CBR system are given, and the results for trials of the system are presented. The competence of the current case-base is discussed, with reference to a representation of cases as points in an n-dimensional feature space, and its principal components visualization. A refinement of the case base is performed as a result of the competence analysis and the performance of the case-base before and after refinement is compared.     

基于范例推理系统的实时道路交通行程安排研究

阐述了CBR的体系结构和开发过程。引用Virginia的hampron路径系统原型,说明了开发实时道路交通行程安排系统的方法与步骤。运用滚动视野法阶段性解决路径分配问题,反复进行路径分配方案的局部优化,使最新的环境信息得到充分利用。构建范例库的范例由一种用于地区的启发式的动态交通分配模型产生,用另外一组范例通过对比它和DTA模型的解来研究评估原型系统的性能。评估结果说明原型系统是能够在实时系统中运行的。     

基于可能性理论的案例决策方法研究

提出基于可能性理论与基于案仍推理相结合的双层CBDT决策方法。第1层：决策者应用基于案例推理方法，通过建立在连续集合上问题的可能性分布，结合不同的决策方法对决策问题的不确定性进行定性分析；第2层：利用期望效用理论在与问题的可能性分布相关联的方案中选择具体方案。该方法可避免以往基于案例决策方法中所蕴含的一些技术难题。     

提高案例推理分类器的可靠性研究

针对案例推理（Case-based reasoning,CBR）分类器的可靠性问题,本文提出一种改进的案例检索和案例重用方法. 首先在案例检索环节应用注水原理对属性权重进行优化分配,利用每个属性数据的标准差和均值构造拉格朗日函数求得属性权重,并设定重要度阈值指导属性约简;其次在案例重用环节引入基于可信度的重用策略,通过计算目标案例分属于各个类别的可信度大小来确定当前案例的分类结果. 最后通过实验对比,表明本文方法能有效提高分类精度和效率,分类器的可靠性得以保障.     

基于实例推理的工程造价估算知识重用模型

针对传统的工程造价估算方法存在过程复杂、对个人的经验依赖性强,以及缺乏估价知识的积累和继承等问题,提出了基于实例推理的工程造价估算知识重用方法。首先建立了能统一实例、实例特征、特征值和解的工程造价估算实例表示模型;然后借助灰色理论,分别提出了基于灰色关联分析的指标权重确定方法和综合了相似性、贴近性的灰色关联度实例配置算法。在实例重用方面,探讨了基于替换策略的相似实例适应性调整方法。最后,通过12个住宅建筑造价估算的应用实例验证了估算知识重用方法的可行性和有效性。结果表明,基于实例推理的知识重用方法能够为及     

Case-based reasoning techniques to support reusability in a requirement engineering and system design tool

CASA (computer aided systems architecting) is a methodology and tool to support the design of complex technical systems. It combines approaches from systems and requirement engineering and AI. System design in CASA is requirement-driven, and works by a hierarchical stepwise top-down refinement of designs and a hierarchical decision-making process. One important task in CASA deals with the reusability of existing design artifacts and is supported by case-based reasoning techniques. Based on given structural specifications and formal requirements, a search procedure finds the best inexact match in a design base and computes an estimated degree of fulfillment for requirements. The approach employs efficient graph-matching and indexing schemes for case retrieval and structural similarities, and has adapted usual similarity measures to compute degree of fulfillment of requirements. It has been shown by different sample projects that the developed methods can be of great practical assistance to a designer.     

基于本体的案例推理模型研究*

提出了基于本体的案例检索及相似性评估方法和基于本体的案例适配模型,使得CBR(case-based reasoning)系统的开发可在语义层次上进行相似性评估和案例适配,这样得到的结果更能反映用户的真实需求;并且CBR所需要的领域知识可从本体中获取,大大降低了传统CBR系统中知识获取的瓶颈。最后在此基础上,提出了基于本体的CBR系统模型框架,从软件复用的角度提高了CBR系统的开发效率。     

基于适应性修改的CBR建库中的数据挖掘

研究了从大量的原始数据中挖掘典型和关键事例以进行CBR事例库建造的问题,指出在不同的数据库结构中,其算法不同,没有一个通用的算法能最好地满足所有的领域。并引用适应性修改的概念提供了在CBR中的关键事例的算法。     

基于案例的推理在增值税纳税申报系统中的应用

将基于案例的推理(CBR)方法应用于增值税纳税申报系统中，收集各种典型增值税案例的处理经验组织成案例库。当遇到实际案例时，以业务特征分类成小案例到案例库中寻找相匹配的案例解答后，再收集计算结果以输出新案例的完整求解方法。     

Hybrid-biomarker case-based reasoning system for water pollution assessment in Abou Hammad Sharkia,Egypt

Water pollution by organic materials or metals is one of the problems that threaten humanity, both nowadays and over the next decades. Morphological changes in Nile Tilapia “Oreochromis niloticus” fish liver and gills can also represent the adaptation strategies to maintain some physiological functions or to assess acute and chronic exposure to chemicals found in water and sediments. This paper presents an automatic system for assessing water quality, in Sharkia Governorate – Egypt, based on microscopic images of fish gills and liver. The proposed system used fish gills and liver as hybrid-biomarker in order to detect water pollution. It utilized case-based reasoning (CBR) for indicating the degree of water quality based on the different histopathological changes in fish gills and liver microscopic images. Various performance evaluation metrics namely, retrieval accuracy, receiver operating characteristic (ROC) curves, F-measure, and G-mean have been used in order to objectively indicate the true performance of the system considering the unbalanced data. Experimental results showed that the proposed hybrid-biomarker CBR based system achieved water quality prediction accuracy of 97.9% using cosine distance similarity measure. Also, it outperformed both SVMs and LDA classifiers for the tested microscopic images dataset.     

基于实例推理的电机模具设计

结合某企业电动机典型零件的模具设计,将实例设计的设计思想用于电机模具设计,同时通过对基于实例推理的分析,成功实现了基于相似实例的模具CAD系统,经实际应用,效果显著。     

Case-based reasoning for classification in the mixed data sets employing the compound distance methods

Development of classification methods using case-based reasoning systems is an active area of research. In this paper, two new case-based reasoning systems with two similarity measures that support mixed categorical and numerical data as well as only categorical data are proposed. The principal difference between these two measures lies in the calculations of distance for categorical data. The first one, named distance in unsupervised learning (DUL), is derived from co-occurrence of values, and the other one, named distance in supervised learning (DSL), is used to calculate the distance between two values of the same feature with respect to every other feature for a given class. However, the distance between numerical data is computed using the Euclidean distance. Furthermore, the importance of numeric features is determined by linear discrimination analysis (LDA) and the weight assignment to categorical features depends on co-occurrence of feature values when calculating the similarity between a new case and the old one. The performance of the proposed case-based reasoning systems has been investigated on the University of California, Irvine (UCI) data sets by 5-fold cross validation. The results indicate that these case-based reasoning systems will produce a proper performance in predictive accuracy and interpretability.     

基于描述逻辑的事例推理综述

基于描述逻辑的事例推理(CBR)是当前CBR研究的热点之一。首先介绍了CBR的起源,然后回顾了基于描述逻辑的CBR的发展历史,接着从4个方面:事例表示与组织、事例检索、事例修正和事例库维护综述了基于描述逻辑的CBR的研究工作,最后指出了基于描述逻辑的CBR目前存在的问题并相应地提出了未来的研究方向。