铁路行车事故救援决策方法研究

传统的铁路行车事故救援多采用人工方式给出救援方案,但事故受多方面因素的影响,救援人员很难及时的给出科学合理的救援方案.针对已有救援知识不完备、不系统的特点,提出规则推理(Rule-based Reasoning,RBR)和案例推理(Case-Based Reasoning,CBR)相结合的两级分层推理框架,给出了系统流程图,说明了RBR与CBR的具体实现方法,并将自组织特征映射网络(Self-Organizing Feature Map,SOFM)应用到事例检索中,有效地提高了检索的效率.仿真实验结果表明系统取得了良好的效果.克服了单一推理的缺点,实现了对救援理论和经验的复用,提高了系统的效率和综合推理能力,并使系统具有了学习能力.研究结果为进一步应用奠定了基础.     

基于案例与规则推理的故障诊断专家系统

设计并实现基于案例的推理(CBR)与基于规则的推理(RBR)的故障旋转机械诊断专家系统。采用CBR与RBR串行方式进行推理,优先通过案例匹配方式寻求诊断结果,在不适用情况下转入通用性规则推理,并将诊断结果反馈给知识库进行优化。应用结果表明,该系统诊断结果与实际相符合,且诊断速度快、针对性强。     

灰度关联理论在CBR中的应用研究

针对基于规则推理技术(RBR)知识获取困难、自学习能力差等缺陷,将基于案例推理技术(CBR)引入故障诊断系统中.介绍了基于案例推理的故障诊断方法的工作机理和过程模型,阐述了案例表示、案例检索、案例保存和案例库维护机制,然后简单介绍了灰色关联理论知识,并把灰色关联理论应用到故障案例相似度的计算中.根据实验结果可知,该方法有效地改进了案例检索算法,提高了故障案例匹配的准确度和检索效率,同时具有较好的分辨率.     

煤矿事故案例本体知识库的构建及推理研究

针对煤矿事故案例知识组织、共享和再利用不足等问题,将本体引入事故案例知识管理中,研究基于本体的事故案例知识库的构建和推理技术。通过分析事故案例知识构建了事故知识表示元组和事故案例元本体。在此基础上,按照知识库模型和构建方法分别构建了事故案例本体库和规则库,从而完成知识库的构建。以瓦斯事故为例实现了基于煤矿事故案例知识库的知识推理应用。研究结果表明,利用所构建的煤矿事故案例知识库能够较好地进行知识组织和知识的自动推理,提高了煤矿事故案例知识的共享和重用。     

灰度关联理论在CBR中的应用研究

针对基于规则推理技术（RBR）知识获取困难、自学习能力差等缺陷,将基于案例推理技术（CBR）引入故障诊断系统中。介绍了基于案例推理的故障诊断方法的工作机理和过程模型,阐述了案例表示、案例检索、案例保存和案例库维护机制,然后简单介绍了灰色关联理论知识,并把灰色关联理论应用到故障案例相似度的计算中。根据实验结果可知,该方法有效地改进了案例检索算法,提高了故障案例匹配的准确度和检索效率,同时具有较好的分辨率。     

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.     

基于案例推理和规则推理的公安突发事件辅助决策算法

为了提高突发事件发生时公安指挥部门处置决策方案的及时性和科学性,本文提出基于案例推理(Case-Based Reasoning, CBR)和规则推理(Rule-Based Reasoning, RBR)的公安突发事件辅助决策算法。算法根据突发事件的级别、类型和突发事件中的具体数据,如伤亡人数等,通过CBR检索出案例库中同级别同类型的最相似案例,再通过RBR对检索案例的结果进行修正优化使之更适用于突发事件的实际情况。最后通过实例成功地验证了该算法。该算法能够为公安应急预案与辅助决策平台的建设提供参考。     

智能环灾应急决策支持技术研究

针对目前环灾应急决策系统中预案信息化程度低、动态应急能力不足的问题,文中在数字化预案的基础上,提出了一套基于案例推理(CBR)和基于规则推理(RBR)相结合的智能辅助决策机制。鉴于环灾应急事件的复杂性,许多应急处置方案都是基于过去的经验,而且应急过程中又随时有可能出现新的应急目标,文中采用了以CBR方法为主,RBR方法为辅的CR智能辅助决策方法。这种方法能更有效地实现复杂环灾应急的辅助决策需要,最后通过某化工园应急决策实例展示了文中所讨论的方法的过程。     

船舶避碰智能决策支持系统研究

建立了一个基于RBR(Case-Based Reasoning,基于案例推理)和CBR(Rule-Based Reasoning,基于规则推理)结合的船舶避碰决策支持模型,将这个模型引入到船舶避碰智能决策支持系统IDSSVCA(Intelligent Decision Support System for Vessel...     

基于事例推理的电路诊断技术研究

本文首先简要介绍了基于事例推理(CBR)和基于规则推理(RBR)的优缺点,其次建立了一个CBR和RBR相结合的电路故障诊断系统,最后说明了该系统的基本结构及设计过程。     

基于混合推理机制的故障诊断专家系统

多数故障诊断专家系统采用单一的推理机制,或者基于规则的推理,或者基于事例的推理。而这两种推理机制都各有优缺点,采用单一推理机制会造成诊断的不准确性。论文将基于规则的推理和基于事例的推理相结合,设计了混合推理机制。在此基础上,论文设计了一个既有专家知识库,又有故障事例库,具有自学习能力的故障诊断专家系统(AFDES)。实验结果表明,论文设计的混合推理机制是比较有效的。     

基于案例推理的教学案例知识管理系统的设计

随着案例教学的研究成为我国教育的一个热点,与此同时,教学案例的管理问题被提上日程。文章阐述了利用案例推理技术（case-base Reasoning）,设计支持教师进行教学案例研究的平台——基于CBR的教学案例知识管理系统。最大限度地方便教师获取他们所需的教学案例知识。     

Knowledge-based treatment planning for adolescent early intervention of mental healthcare: a hybrid case-based reasoning approach

Abstract: Treatment planning is a crucial and complex task in the social services industry. There is an increasing need for knowledge-based systems for supporting caseworkers in the decision-making of treatment planning. This paper presents a hybrid case-based reasoning approach for building a knowledge-based treatment planning system for adolescent early intervention of mental healthcare. The hybrid case-based reasoning approach combines aspects of case-based reasoning, rule-based reasoning and fuzzy theory. The knowledge base of case-based reasoning is a case base of client records consisting of documented experience while that for rule-based reasoning is a set of IF–THEN rules based on the experience of social service professionals. Fuzzy theory is adopted to deal with the uncertain nature of treatment planning. A prototype system has been implemented in a social services company and its performance is evaluated by a group of caseworkers. The results indicate that hybrid case-based reasoning has an enhanced performance and the knowledge-based treatment planning system enables caseworkers to construct more efficient treatment planning in less cost and less time.     

建造和丰富武器故障诊断专家系统的知识库

为了模拟现实专家的诊断过程,计算机专家系统中将知识分为原理知识和经验知识,对应的诊断为原理诊断和经验诊断。文中介绍了获取有关电子类设备故障诊断时所需原理知识和经验知识的基本方法,分析了原理诊断和经验诊断之间的关系,进而研究了专家系统的一种自学习新方法CBR,即把原理诊断的成功案例当作知识源,通过对案例进行学习,从而获取经验知识,完善经验知识库,在后续的诊断中可以大量节约诊断成本。这种方法较好地模拟了现实专家的诊断过程。同时对丰富类似的专家系统的经验知识库的知识,有参考价值。     

基于案例和模糊推理的农业虫害专家系统研究

为了满足实.际虫害诊断问题对专家系统的要求,根据虫害特征诊断的现实特点和要求,首次将模糊技术和案例推理相融合,引入到虫害诊断专家系统的设计中.阐述了模糊案例推理的知识表示,给出了模糊案例推理技术的推理过程,提出了基于案例与模糊推理的虫害诊断推理机制.对二者的结合方式做了阐述,给出了专家系统的整体实现结构,并时各个模块的实现方法进行了详尽的阐述,最终以一个实例演示了实例诊断的流程.     

Data mining technique for medical informatics: detecting gastric cancer using case-based reasoning and single nucleotide polymorphisms

Abstract: Although data mining and knowledge discovery techniques have recently been used to diagnose human disease, little research has been conducted on disease diagnostic modelling using human gene information. Furthermore, to our knowledge, no study has reported on diagnosis models using single nucleotide polymorphism (SNP) information. A disease diagnosis model using data mining techniques and SNP information should prove promising from a practical perspective as more information on human genes becomes available. Data mining and knowledge discovery techniques can be put to practical use detecting human disease, since a haplotype analysis using high-density SNP markers has gained great attention for evaluating human genes related to various human diseases. This paper explores how data mining and knowledge discovery can be applied to medical informatics using human gene information. As an example, we applied case-based reasoning to a cancer detection problem using human gene information and SNP analysis because case-based reasoning has been applied in medicine relatively less often than other data mining techniques. We propose a modified case-based reasoning method that is appropriate for associated categorical variables to use in detecting gastric cancer.     

基于实例的推理在直升机故障诊断专家系统中的应用

提出了基于实例的故障诊断专家系统方案：用产生式规则描述故障诊断单元知识,采用子空间划分法进行知识规划,基于实例的知识表达、推理机制和学习系统,推理过程中的“黑板法”等。目前基于实例的某型直升机故障诊断专家系统已经投入使用,能够适应当前该型直升机诊断、维修和排故的需求,具有良好的推广应用价值。     

Automating the Diagnosis and Rectification of Deflection Yoke Production Using Hybrid Knowledge Acquisition and Case-Based Reasoning

Deflection yoke (DY) is one of the main components of the color display tube (CDT) that determines the image quality of a computer monitor. Once a DY anomaly is found during production, the remedy process is performed in two steps: identifying the type of anomaly from the observed problem pattern and adjusting manufacturing process parameters to rectify it. To support this process, we introduce a knowledge-based system using a hybrid knowledge acquisition technique and case-based reasoning. The initial phase of the knowledge acquisition employs a systematic and quantitative data processing including stepwise regression and an inductive learning algorithm. This automated expertise elicitation produces strategies, which are represented by decision trees or if-then rules, to specify DY anomalies from display patterns. The strategies are then refined by introducing human expertise. The knowledge acquisition process was designed to support for this cognitive cooperation. For coordinating the process parameters to remedy the specified anomalies, a case-based reasoning is utilized. The laboratory and field test proved that the developed knowledge-based system could produce highly effective decisions for the process control in DY production.     

Towards a Knowledge-Level Model of Context and Context Use in Diagnostic Problems

Diagnostic support systems that help solving problems in open and weak theory domains need to be context-sensitive in order to reveal flexible and efficient behaviour. This paper presents a task-oriented methodology for analysing and modeling contextual knowledge at the knowledge level. We present a context-sensitive diagnosis approach (ConSID) which clarifies the connection between content and process knowledge. The former embodies the domain model, while the latter embodies the task and method models. We present a prototypical system, the ConSID-Creek, that applies the ConSID approach to the medical diagnostic domain. We illustrate how the system integrates case-based and explanation-based reasoning paradigms when realizing the abductive subtask of the overall diagnostic task.