基于知识工程的岸浅桥数字化样机设计系统

提出了一种岸边集装箱起重机的数字化设计方法,这种方法以专家系统和模犁库为支撑,构建基于知识工程的岸边集装箱设计系统.论述了数据库和计算方法为基础的专家系统,并且讨论了模型库的结构,标准件、外购件的选择方法.由基础设计参数、设计约束、设计规则寻找最适合的型号和尺寸驱动模型.通过计算后的数据到专家系统中寻找型号,再从模型库...     

案例推理在果树病虫害诊断与防治专家系统的研究

根据果树病虫害诊断与防治的特点和要求,将案例推理技术引入到果树病虫害诊断与防治专家系统设计中。阐述了案例推理概念和工作过程,在具体应用中提出了案例知识表示、两层的案例库组织结构和检索推理机制,得出基于案例推理果树病虫害诊断与防治专家系统实现算法流程。该系统在实际应用中获得了较好的效果。     

基于案例的大型项目研制风险评估专家系统

针对大型项目研制风险评估的实际和评估过程,该文引入基于案例的专家系统对大型项目研制风险进行评估,建立了构建专家系统的基本框架,讨论了风险案例库建立的过程和基于案例的推理机制,为建立智能化的评估专家系统做了探索性尝试。     

案例推理在果树病虫害诊断与防治专家系统的研究

根据果树病虫害诊断与防治的特点和要求，将案例推理技术引入到果树病虫害诊断与防治专家系统设计中。阐述了案例推理概念和工作过程，在具体应用中提出了案例知识表示、两层的案例库组织结构和检索推理机制，得出基于案例推理果树病虫害诊断与防治专家系统实现算法流程。该系统在实际应用中获得了较好的效果。     

基于案例的推理在农业专家系统中的应用

该文将基于案例的推理方法CBR应用到农业专家系统中。在对CBR方法作了简单介绍后,提出了在农业专家系统中面向对象的案例表示、案例库组织的两层结构,并以大豆专家系统中病虫害诊断模块为例阐述了CBR推理在农业专家系统中的具体实现过程。     

基于CBR和XML的软构件检索方法

在对现有构件检索方法分析的基础上,探讨了一种基于案例推理和XML技术的智能化软件构件的检索框架。重点阐述了构件案例库中构件的XML知识表示方法以及构件检索中需求构件和案例库中构件的相似度评估方法,提出了一种计算案例相似度的递归算法。     

基于数据挖掘技术的飞机故障诊断专家系统设计

为适应现代民用飞机故障诊断的需求,应用飞机故障诊断历史经验,构建了飞机故障诊断维修知识库,在此基础上,研究了依据飞机维护历史经验知识和数据挖掘技术的故障诊断方法;应用关联分析方法实现了维修历史库的挖掘诊断,通过案例库的聚类分析,显著提高了案例库的检索效率;针对某型民机地面故障诊断的任务要求,设计了基于数据挖掘的机载设备故障诊断专家系统;通过输入真实故障信息,运行专家系统进行诊断分析,验证了所实现的基于数据挖掘的故障诊断专家系统具有较高的准确性。     

基于案例的RCM分析系统案例库的设计

案例库是基于案例的以可靠性为中心的维修(RCM)分析系统的核心,其内容和结构对系统推理效率具有重要的影响。介绍了基于案例的RCM分析系统,提出了案例库的设计目标,分析了案例的主要成份构成,阐述了面向对象、基于关系数据库的案例库组织形式以及索引机制。案例库的设计为基于案例的RCM分析系统的开发和实现奠定了坚实的基础。     

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。     

基于案例推理的信息系统业务流程知识重用技术研究

本文在研究信息系统业务流程设计的知识表示与重用技术的基础上,提出了一种基于案例的智能化设计知识重用方法进行信息系统业务流程设计.重用方法包含案例表示、基于相似度算法和智能聚类的案例检索、案例优化、案例库组织四个方面.综合四个方面,实现了基于案例推理的业务流程案例检索和知识重用实验系统原型,并进行了实验.实验结果表明本重用方法具有较好的可行性、有效性、效率与质量.     

一种CBR与RBR相结合的快速预案生成系统

将范例推理(case based reasoning,CBR)与规则推理(rule based reasoning, RBR)两种人工智能技术相结合,实现一种快速预案生成系统.它有效地解决了单纯RBR系统在预案生成过程中的时间延迟缺陷和知识库难以获取的瓶颈.通过CBR工具,能够把以前发生的紧急事件和解决方案生成预案.一旦新的事件发生,首先从预案库中进行案例的相似性检索,如果没有检索到预案或者检索到的预案匹配度很低,再采用RBR系统对紧急事件进行规则推理,然后把推理结果重新存入预案库.实验数据表明,这种方法对单纯RBR系统在时间响应上进行了有效的优化.另外,因为案例的获取比专家系统推理规则的获取容易得多,它同时解决了RBR系统推理规则难以获取的瓶颈.根据这种思想,实现了CBR与RBR结合的快速预案生成系统.目前,它已经应用到抗洪抢险的预案生成和城市应急联动的决策支持上,效果表明它在预案生成速度以及实际可操作性上都具有明显优势.     

基于案例推理的纺纱工艺智能设计

针对工艺设计系统在一定程度上依赖于专家知识和以往经验的特点,将基于案例推理引入到纺纱工艺设计中,提出了一套基于CBR的智能化工艺设计系统,介绍了工艺案例之间的相似性度量算法。并讨论了案例库（casebase）的维护。实际应用结果表明,该智能设计系统有效地提高了工艺设计的效率和准确性,缩短了产品开发周期,具有重要的应用价值。     

Data/knowledge representation of modular robot and its working environment

This paper reports a work towards automating the design of a modular robot in the manufacturing environment. As the first as well as the most important step, a data model or data representation of all the design related information needs to be developed. This paper discusses the data representation of information needed for the computer to automatically generate a suitable modular robot configuration. A modular robot is supposed to work in a manufacturing assembly environment. Therefore, the collection of the information needed starts from such an environment. The information is further derived based on a proposed architecture of the computer-aided system for generating a modular robot configuration, which is based on two theories, i.e., cased-based reasoning and function-behaviour-structure (FBS). As a consequence, an integrated data representation of both modular robot and its environment is proposed and discussed in this paper. The integrated data representation also implies that function, behaviour and structure are related to a modular robot (as well as modular joint) are represented in the computer. EXPRESS data modelling language is used to complete the modelling work, and is found necessary for complex systems. A case study has been provided to show the capability of the developed data representations.     

Decision Planning Knowledge Representation Framework: A Case-Study

This paper discusses experiences and perspectives of utilisation of declarative knowledge structures as a convenient knowledge base medium in configuration expert systems. Although many successful systems have been developed, these are often difficult to maintain and to generalize in rapidly changing domains. In this paper we address the problem of building intelligent knowledge based systems with emphasis on their maintainability. Firstly, several industrial applications of proof planning, a theorem proving technique, will be described and their advantages and flaws will be discussed. This discussion is followed by the theoretical foundation of decision planning knowledge representation framework that, based on proof planning, facilitates separate administration of inference problem solving knowledge and the domain theory axioms. Machine learning methods for maintaining the inference knowledge to be up-to-date with permanently changing domain theory are commented and evaluated.     

ASHSD-II: A computational model for litigation support

Abstract: In this paper a hybrid knowledge-based system which exploits both rule-based reasoning (RBR) and case-based reasoning (CBR) is presented. The issues of RBR and CBR in general in the context of legal knowledge-based systems and legislation in rule form and previously-decided cases in an interconnected graph form are discussed. It is possible for the user to select either reasoning method (RBR or CBR), or indicate no preference. The rule base of this system consists of two types of rule. The first type of rule determines which options are legally applicable. The second type indicates how the courts are likely to act within the range of options available, which is determined by the first type of rule. When CBR is selected, the system uses the features of previously-decided cases to select the most similar cases to the situation that is described in the input and displays their details of decisions. In case of the selection of no preference option, the system applies RBR and CBR method separately, and then presents results based on an automated relative rating of the qualities of the RBR (based on the second type of rules) and CBR advice. These ideas have been implemented in a prototype system, known as A dvisory S upport for H ome S ettlement in D ivorce (ASHSD-II).     

基于模糊粗糙集的设计实例库维护方法及应用

实例库维护是基于实例的推理方法中的一项核心工作,目前国内外关于实例库维护方法的研究还存在一些不足.针对机械产品设计实例的特点,提出一种基于模糊粗糙集理论的实例库维护方法.首先定义了产品设计实例特征权重计算、实例库族集的划分以及实例属性的约简方法;在此基础上,引入覆盖度和可触及方法对典型实例进行筛简.最后开发了面向工程机械设计的实例库维护系统,并给出了具体应用效果.     

基于投影寻踪和MapReduce的并行案例推理模型

在大规模、高维度的数据环境下,传统的案例推理具有计算复杂度高、实时性差等缺点。为在大数据环境下进行案例推理,提出了一种基于投影寻踪和MapReduce的并行推理模型dpCBR。在数据预处理阶段,计算源案例到基准向量的一维投影距离并缓存,降低计算复杂度并减少重复计算开销。在案例检索阶段,先根据投影距离裁剪案例库,再进行相似度匹配,减少不必要的案例匹配开销。应用MapReduce进行分布式并行处理,使dpCBR具备对大规模案例库的推理能力。实验结果表明,dpCBR模型可以明显提高大数据环境下案例推理的效率。