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Lynn Ling X Li 《Expert Systems》1999,16(4):248-256
Although many knowledge-based systems (KBSs) focus on single-paradigm approaches to encoding knowledge (such as production rules), experts rarely use a single type of knowledge in solving a problem. More often, an expert will apply a number of reasoning mechanisms. In recent years, rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) have emerged as important and complementary reasoning methodologies in artificial intelligence. For complex problem solving, it is useful to integrate RBR, CBR and MBR. In this paper, a hybrid KBS which integrates a deductive RBR system, an inductive CBR system and a quantitative MBR system is proposed for epidemic screening. The system has been tested using real data, and results are encouraging. 相似文献
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Although many knowledge-based systems (KBSs) focus on single-paradigm approaches to encoding knowledge (such as production rules), human experts rarely use a single type of knowledge to solve a real-world problem. A human expert usually combines a number of reasoning mechanisms. In recent years, rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) have emerged as important and complementary reasoning methodologies in the intelligent systems area. For complex problem solving, it is useful to integrate RBR, CBR and MBR. In this paper, a hybrid epidemic screening KBS which integrates a deductive RBR system, an inductive CBR system and a quantitative MBR system is proposed. The system has been tested using real epidemic screening variables and data. 相似文献
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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). 相似文献
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Although case-based reasoning (CBR) was introduced as an alternative to rule-based reasoning (RBR), there is a growing interest in integrating it with other reasoning paradigms, including RBR. New hybrid approaches are being piloted to achieve new synergies and improve problem-solving capabilities. In our approach to integration, CBR is used to satisfy multiple numeric constraints, and RBR allows the performance of "what if" analysis needed for creative design.
The domain of our investigation is nutritional menu planning. The task of designing nutritious, yet appetizing, menus is one at which human experts consistently outperform computer systems. Tailoring a menu to the needs of an individual requires satisfaction of multiple numeric nutrition constraints plus personal preference goals and aesthetic criteria.
We first constructed and evaluated independent CBR and RBR menu planning systems, then built a hybrid system incorporating the strengths of each system. The hybrid outperforms either single strategy system, designing superior menus, while synergistically providing functionality that neither single strategy system could provide. In this paper, we present our hybrid approach, which has applicability to other design tasks in which both physical constraints and aesthetic criteria must be met. 相似文献
The domain of our investigation is nutritional menu planning. The task of designing nutritious, yet appetizing, menus is one at which human experts consistently outperform computer systems. Tailoring a menu to the needs of an individual requires satisfaction of multiple numeric nutrition constraints plus personal preference goals and aesthetic criteria.
We first constructed and evaluated independent CBR and RBR menu planning systems, then built a hybrid system incorporating the strengths of each system. The hybrid outperforms either single strategy system, designing superior menus, while synergistically providing functionality that neither single strategy system could provide. In this paper, we present our hybrid approach, which has applicability to other design tasks in which both physical constraints and aesthetic criteria must be met. 相似文献
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规则推理和案例推理的集成研究 总被引:15,自引:1,他引:15
基于规则的推理(RBR)和基于案例的推理(CBR)是知识或两类实用有效的推理方式,文中提出了一种RBR与CBR相互集成的方法,为消除CBR和RBR结果之间的冲突,引入了逆案例,隐含规则和相似性度量等概念,以此提高了系统求解问题的效率,增强了系统对不良结构问题的适应性。 相似文献
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一种CBR与RBR相结合的快速预案生成系统 总被引:3,自引:0,他引:3
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. 相似文献
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Gaoliang Peng Guangfeng Chen Chong Wu Hou Xin Yang Jiang 《Expert systems with applications》2011,38(1):26-38
A fixture is a special tool used to accurately and stably locate the workpiece during machining process. Proper fixture design improves the quality and production of parts and also facilitates the interchangeability of parts that is prevalent in much of modern manufacturing. This study combines the rule-based reasoning (RBR) and case-based reasoning (CBR) method for machining fixture design in a VR based integrated system. In this paper, an approach combines the RBR and fuzzy comprehensive judgment method is proposed for reasoning suitable locating schemes and locating features. Based on the reasoning results, a CBR method for machining fixture design is then presented. This method could help designers, by referencing previous design cases, to make a conceptual fixturing solution quickly. Finally, the implementation of proposed system is outlined and cases study has been used to demonstrate the applicability of the proposed approach. 相似文献
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CBR与RBR相结合的实时专家系统设计与实现 总被引:12,自引:0,他引:12
提出了一个基于案例的推理与基于规则的推理相结合的实时专家系统RTESCR,介绍了该系统原理及其组成部分。RTESCR主要适用于知识富有型应用领域,目前应用于航天控制系统实时故障诊断系统。 相似文献
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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。 相似文献
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支持概念及装配建模的智能变型设计系统框架 总被引:12,自引:0,他引:12
概述了目前计算机辅助变型设计中存在的问题,将实例推理技术(CBR)应用于变型设计,提出了一个支持概念建模和装配建模的智能变型设计系统框架,研究了这种智能变型设计的设计过程理论,并对系统的关键技术-实例的表示和了详细的研究。 相似文献
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信息系统总体设计中案例推理与规则推理集成方法的研究 总被引:7,自引:1,他引:7
通过对信息系统总体方案设计任务特点的分析和对案例推理与规则推理优、缺点的比较,提出一种信息系统总体设计的案例推理与规则推理相结合的集成推理方法,可以提高信息系统总体设计的效率和质量。 相似文献
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《Computers & Industrial Engineering》2013,64(4):1107-1117
Statistical process control (SPC) is a sub-area of statistical quality control. Considering the successful results of the SPC applications in various manufacturing and service industries, this field has attracted a large number of experts. Despite the development of knowledge in this field, it is hard to find a comprehensive perspective or model covering such a broad area and most studies related to SPC have focused only on a limited part of this knowledge area. According to many implemented cases in statistical process control, case-based reasoning (CBR) systems have been used in this study for developing of a knowledge-based system (KBS) for SPC to organize this knowledge area. Case representation and retrieval play an important role to implement a CBR system. Thus, a format for representing cases of SPC and the similarity measures for case retrieval are proposed in this paper. 相似文献
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A case-based reasoning system development for statistical process control: Case representation and retrieval 总被引:1,自引:0,他引:1
Statistical process control (SPC) is a sub-area of statistical quality control. Considering the successful results of the SPC applications in various manufacturing and service industries, this field has attracted a large number of experts. Despite the development of knowledge in this field, it is hard to find a comprehensive perspective or model covering such a broad area and most studies related to SPC have focused only on a limited part of this knowledge area. According to many implemented cases in statistical process control, case-based reasoning (CBR) systems have been used in this study for developing of a knowledge-based system (KBS) for SPC to organize this knowledge area. Case representation and retrieval play an important role to implement a CBR system. Thus, a format for representing cases of SPC and the similarity measures for case retrieval are proposed in this paper. 相似文献
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Multi-Modal Reasoning medical diagnosis system integrated with probabilistic reasoning 总被引:1,自引:0,他引:1
Jia Tian Xun Chen School of Mechanical Materials Manufacturing Engineering Management University of Nottingham University Park NG RD UK Sheng-Ping Dong Exhibition Road Hospital Xi Cheng District Beijing PRC 《国际自动化与计算杂志》2005,2(2):134-143
In this paper, a Multi Modal Reasoning (MMR) method integrated with probabilistic reasoning is proposed for the diagnosis support module of the open eHealth platform. MMR is based on both Rule Based Reasoning (RBR) and Case Based Reasoning (CBR). It is not only applied to the identification of diseases and syndromes based on medical guidelines, but also deals with exceptional cases and individual therapies in order to improve diagnostic accuracy. Moreover, a new rule expression frame is introduced to deal with uncertainty, which can represent and process vague, imprecise, and incomplete information. Furthermore, this system is capable of updating the attributes of rules and inducing rules with a small data sample. 相似文献
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Sohail Sarwar Zia Ul-Qayyum Owais Ahmed Malik 《Expert systems with applications》2012,39(2):1626-1636
Cache being the fastest medium in memory hierarchy has a vital role to play for fully exploiting available resources, concealing latencies in IO operations, languishing the impact of these latencies and hence in improving system response time. Despite plenty of efforts made, caches alone cannot comprehend larger storage requirements without prefetching. Cache prefetching is speculatively fetching data to restrain all delays. However, effective prefetching requires a strong prediction mechanism to load relevant data with higher degree of accuracy. In order to ameliorate the predictive performance of cache prefetching, we applied the hybrid of two AI approaches named case based reasoning (CBR) and artificial neural networks (ANN). CBR maintains the past experience and ANN are used in adaptation phase of CBR instead of employing static rule base. The novelty of technique in this domain is valued due to hybrid of two approaches as well as usage of suffix tree in populating the CBR’s case base. Suffix trees provide rich data patterns for populating case base and greatly enhanced the overall performance. A number of evaluations from different aspects with varying parameters are presented (along with some findings) where the efficacy of our technique is affirmed with improved predictive accuracy and reduced level of associated costs. 相似文献