共查询到20条相似文献,搜索用时 171 毫秒
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相对于静态的知识,定义了基于可拓变换的可拓知识,可拓知识是变化的知识.在可拓知识定理(从知识中获取可拓知识)和可拓推理公式的基础上,证明了基于集合的可拓知识定理和基于本体的可拓知识链定理.通过实例,在多维层次数据中,获取问题产生原因的可拓知识链. 相似文献
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基于可拓规则的故障诊断专家系统推理机的研究 总被引:1,自引:0,他引:1
针对传统产生式规则在知识表示、匹配冲突等方面存在的局限,提出了一种将可拓规则用于故障诊断专家系统推理机的方法;该方法重点研究了可拓规则的匹配原理和可拓推理机算法思想,提出了匹配度计算方法并用来计算故障条件与规则前件的匹配度;根据研究表明,利用可拓规则进行推理,不仅在知识表示上比传统产生式规则推理有所提高,而且还解决了传统专家系统容易出现匹配冲突等问题;最后以AMU故障推理为例,说明可拓推理机具有推理速度快、效率高等优点,取得了较好的推理效果. 相似文献
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可拓信息-知识-智能形式化体系研究 总被引:1,自引:0,他引:1
利用可拓论和可拓方法,把信息、知识和智能统一在一个形式化体系中,用可拓推理和可拓变换,去建立生成策略的推理规则,把可拓集合和关联函数作为策略生成和策略评价的定量化工具,探讨建立“可拓信息-知识-智能形式化体系”.给出了建立该体系的框架和主要功能模块.这一研究为利用计算机辅助解决矛盾问题提供可行的工具,为提高计算机的智能化水平创造基础条件. 相似文献
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阐述了可拓数据挖掘概念和矛盾问题的形式化模型,研究了可拓数据挖掘方法过程及解决矛盾问题的方法,并通过实例进行了说明,得出应用可拓数据挖掘解决矛盾问题的策略可以为技术实现策略生成探索出一条可行之路。 相似文献
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可拓数据挖掘的概念与理论 总被引:2,自引:0,他引:2
论文从数据挖掘概念和理论拓宽到可拓数据挖掘概念和理论,证明了两个可拓数据挖掘定理,并通过实例说明可拓数据挖掘是:在数据挖掘中获取的知识的基础上,通过可拓变换,获取可拓变换规则知识(变化知识)。 相似文献
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PROTOTYPICAL CASES FOR RETRIEVAL, REUSE, AND KNOWLEDGE MAINTENANCE IN BIOMEDICAL CASE-BASED REASONING 总被引:1,自引:0,他引:1
Representing biomedical knowledge is an essential task in biomedical informatics intelligent systems. Case-based reasoning (CBR) holds the promise to represent contextual knowledge in a way that was not possible before with traditional knowledge-based methods. One main issue in biomedical CBR is dealing with the rate of generation of new knowledge in biomedical fields, which often makes the content of a case base partially obsolete. This article proposes to make use of the concept of prototypical case to ensure that a CBR system would keep update with current research advances in the biomedical field. Prototypical cases have served various purposes in biomedical CBR systems, among which to organize and structure the memory, to guide the retrieval as well as the reuse of cases, and to serve as bootstrapping a CBR system memory when real cases are not available in sufficient quantity and/or quality. This paper emphasizes the different roles prototypical cases can play in CBR systems, and presents knowledge maintenance as a very important novel role for these prototypical cases. 相似文献
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《Knowledge and Data Engineering, IEEE Transactions on》2001,13(5):793-812
Case based reasoning (CBR) is an artificial intelligence technique that emphasises the role of past experience during future problem solving. New problems are solved by retrieving and adapting the solutions to similar problems, solutions that have been stored and indexed for future reuse as cases in a case-base. The power of CBR is severely curtailed if problem solving is limited to the retrieval and adaptation of a single case, so most CBR systems dealing with complex problem solving tasks have to use multiple cases. The paper describes and evaluates the technique of hierarchical case based reasoning, which allows complex problems to be solved by reusing multiple cases at various levels of abstraction. The technique is described in the context of Deja Vu, a CBR system aimed at automating plant-control software design 相似文献
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为了提高Tennessee-Eastman(TE)过程的故障诊断准确率,本文研究一种学习型伪度量(learning pseudo metric,LPM)代替距离度量的案例检索方法,并建立了TE过程的案例推理(case-based reasoning,CBR)故障诊断模型.首先建立LPM度量准则并对LPM模型进行训练,其次度量目标案例与每一个源案例的相似度,从中检索与目标案例相似的同类案例,再采用多数重用原则从同类案例中决策出目标案例的解,最后通过TE过程的运行数据对该方法的性能进行测试,并与典型的CBR和BP(back-propagation)神经网络和支持向量机等方法进行对比,表明本文方法能有效提高故障诊断准确率,在实际化工过程中具有一定的推广应用价值. 相似文献
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基于本体的案例推理模型研究* 总被引:2,自引:0,他引:2
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。 相似文献
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The development of an image-processing (IP) application is a complex activity, which can be greatly alleviated by user-friendly graphical programming environments. The major objective of the work described in this paper is to help IP experts reuse parts of their applications. A first step towards knowledge reuse has been to propose a suitable representation of the strategies of IP experts by means of IP plans (trees of tasks, methods and tools). This paper describes the CBR module of an interactive system for the development of IP plans. After a brief presentation of the overall architecture of the system and its other modules, the authors explain the distinction between an IP case and an IP plan, and give the selection criteria and functions that are used for similarity calculation. The core of the CBR module is a search/adaptation algorithm, whose main steps are detailed: retrieval of suitable cases, recursive adaptation of the selected one and memorization of new cases. The system’s implementation is presently completed; its functioning is described in a session showing the kind of assistance provided by the CBR module during the development of a new IP application. 相似文献
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The knowledge stored in a case base is central to the problem solving of a case-based reasoning (CBR) system. Therefore, case-base maintenance is a key component of maintaining a CBR system. However, other knowledge sources, such as indexing and similarity knowledge for improved case retrieval, also play an important role in CBR problem solving. For many CBR applications, the refinement of this retrieval knowledge is a necessary component of CBR maintenance. This article focuses on optimization of the parameters and feature selections/weights for the indexing and nearest-neighbor algorithms used by CBR retrieval. Optimization is applied after case-base maintenance and refines the CBR retrieval to reflect changes that have occurred to cases in the case base. The optimization process is generic and automatic, using knowledge contained in the cases. In this article we demonstrate its effectiveness on a real tablet formulation application in two maintenance scenarios. One scenario, a growing case base, is provided by two snapshots of a formulation database. A change in the company's formulation policy results in a second, more fundamental requirement for CBR maintenance. We show that after case-base maintenance, the CBR system did indeed benefit from also refining the retrieval knowledge. We believe that existing CBR shells would benefit from including an option to automatically optimize the retrieval process. 相似文献
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Information Technology (IT) solutions to problems in construction design need to consider the perspectives of all the participants in the process; only then can IT provide a platform for integration. The research described examines issues involved in the integration of construction disciplines by using Case-Based Reasoning (CBR). It describes a hierarchical case memory structure and a context-based indexing method for retrieval and reuse of previous designs and their costs. Estimating and design cases selected for reuse are adapted with the use of sub-cases and domain specific adaptation rules. A prototype system, NIRMANI, was successfully implemented to support collaborative design. 相似文献
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Extended object model for product configuration design 总被引:1,自引:1,他引:0
This paper presents an extended object model for case-based reasoning (CBR) in product configuration design. In the extended object model, a few methods of knowledge expression are adopted, such as constraints, rules, objects, etc. On the basis of extended object model, case representation model for CBR is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of CBR in product configuration design, such as case representation, indexing, retrieving, and case revising. The presented model is an extension of the traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, and solution class used in case revising. Therefore, the product configuration knowledge used in the product configuration design can be represented by using this model. In the end, a metering pump product configuration design system is developed on the basis of the proposed product configuration model to support customized products. 相似文献
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《Expert systems with applications》2005,28(1):43-53
Unstructured intangible experiences and knowledge are usually difficult to represent and instantiate, which engenders the hardship of knowledge transfer and sharing. Past marketing plans are such valuable documents containing strategic planning knowledge and experiences.Case-Based Reasoning (CBR), which consists of retrieving, reusing, revising, and retaining cases, has been proved effective in retrieving information and knowledge from prior situations and being widely researched and applied in a great variety of problem territories.This paper targets at designing a CBR architecture and a method that facilitate the sharing and retrieving of cases of great concern to the marketing personnel. After an intensive survey of CBR methods and applications, a CBR system embedding multi-attribute decision making method, which provides both overall similarity level and similarity level of each selected attribute, is proposed to enhance the adaptation of a new marketing plan. In addition, a multi-attribute gap analysis diagram is developed to visualize the similarity along with the gap between candidate and target cases, so as to better support interaction and group decision making in the process of strategically formulating a new marketing plan. The CBR system was implemented and successfully demonstrated on case retrieval of a telecommunication company. 相似文献