介绍了专家系统的具体实现过程，对基于规则、基于案例、基于模型以及混合推理的推理机制进行了研究。
It introduces the concrete realization course of the expert system and traverses the inference mechanism based on rule, case, model and hybrid reasoning.
为了实现实验操作的正确性检查，采用产生式系统定义实验规则，使用正向推理策略进行规则匹配。
To implement the check-up of the operations, production system is used to define the experimental rules, and forward reasoning strategy is used for rule match.
专家系统用规则来代表专家，推理并得到合理的解决方案。
Expert systems use rules to represent experts, reasoning in solving problems.
本文运用了将知识库、规则库与推理机分离的思想，使系统更易于维护。
According to the idea of separating repository, regulation base and inference engine, this system will be managed easily.
论文提出一种模糊强化学习算法，通过模糊推理系统将连续的状态空间映射到连续的动作空间，然后通过学习得到一个完整的规则库。
In this paper, we propose a fuzzy reinforcement algorithm, which map continuous state Spaces to continuous action Spaces by fuzzy inference system and then learn a rule base.
本系统知识库中的知识分为事例知识和推理规则知识。
The knowledge within this system knowledge base is divided into the case knowledge and reasoning rule knowledge.
首先，提出一种模糊Q学习算法，通过模糊推理系统将连续的状态空间映射到连续的动作空间，然后通过学习得到一个完整的规则库。
A fuzzy Q learning algorithm is proposed in this dissertation, which map continuous state Spaces to continuous action Spaces by fuzzy inference system and then learn a rule base.
林火蔓延多模型预测系统是根据产生式规则为推理原则建立的多模型预测系统。
The multi-models forecast system for the forest fire spread acts according to the production rule for the inference principle establishment.
自适应神经网络模糊推理系统(ANFIS)能基于数据建模，无须专家经验，自动产生模糊规则和调整隶属度函数。
Applying Adaptive Neural-Fuzzy Inference System (ANFIS) can produce fuzzy rules and adjust membership functions automatically based on data without experience of experts.
最后，以自动门为应用对象，采用规则诊断与贝叶斯诊断集成推理技术，开发了自动门智能故障诊断系统。
Finally, taking ADRT as the application object, using the integrated inference technology of rule diagnosis and Bayesian Network diagnosis methods, we develop the intelligent fault diagnosis system.
领域本体各种关联及其推理规则为智能化教学系统实现智能学习导航提供了理论依据。
Multifarious relation and reasoning rule of Domain-specific Ontology provided theory elements for learning navigation of Intelligent tutoring systems.
与传统的基于规则的系统相比，基于案例推理的系统具有简化知识获取、便于知识积累等优点。
Comparing to traditional rule-based system, it has many advantages, which can predigest knowledge gathering and accumulate knowledge easily.
在系统实现中，采用隶属函数来反映故障对象特征的模糊性和模糊关系，基于关系数据库进行知识的模糊表达，实现基于规则的模糊推理。
In the implement of system, we use membership function to mirror faults fuzzy and fuzzy concern, relational database to describe knowledge and rules, and perform ruled-based inference.
文章介绍了一个港口门机故障检测系统，着重讨论了在采样信号预处理的基础上，通过规则推理进行故障分析的方法。
This paper introduces a fixed crane faults diagnosis system used in port, and focuses on the method of inferring rule based on the pretreatment of sampling signal.
规则式专家系统效率的提高方法，包括推理机和知识库设计及与其他先进技术结合等三个方面。
The methods of improving efficiency of rule-type expert system include the reasoning machine design, knowledge base design and the integration with other advanced technologies.
本文从BIT设计的角度，以功能角色模型理论为基础，导出在反馈系统中的推理规则和故障模式影响分析方法。
In this paper, based on the functional role model theory, the reasoning rule and the technique of FMEA, which are facing to Built in Test (BIT), are developed.
整个网络既有神经网络的学习能力，又有模糊系统的基于规则的推理能力，特别是对子类的自动聚类能力。
The whole network has not only the learning ability to neural network, but also the logic ability to fuzzy system based on rules, especially the automatic clustering ability to sub-class.
利用这些规则对数据库系统返回给普通用户的数据动态地做最小修改，防止推理通道的产生。
According to these relations, rules of inference control are generated and used to modify the data queried by generic users dynamically and most parsimonious ly so as to eliminate inference channels.
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。
Most fault diagnosis expert system adopted single reasoning mechanism, or rule-based reasoning or case-based reasoning.
分析了当前基于规则的专家系统存在的问题，介绍了基于案例推理（CBR）的概念。
The features and problems of the current rule_based expert systems is firstly summarized, and then an introduction to Case_Based Reasoning (CBR)is given.
对于智能系统中的两种推理机制，即正向规则推理和类比推理，进行了较详细的描述。
Two kinds of reasoning mechanism, the forward regular reasoning and the reasoning from analogy, are described in detail.
模糊控制技术能利用控制规则，模拟人脑的推理过程，通过对输入量模糊化和综合推理，可以弱化数据不准确对系统的影响。
Fuzzy control technologies that apply control rules to simulating the inference process of man's brain can diminish the affect on the system by data inaccuracy.
此外，还讨论了系统推理机推理规则的设计原理与组织方法及推理算法。
Furthermore, the author also discusses the design principles and organization method of the inference rules and the inference algorithms of inference engine in the system.
但具有大规模规则库的产生式系统，其知识的组织与管理越来越困难，推理效率也越低。
But as to the large of knowledge data base, it becomes more and more difficult for the organization and management of knowledge, so the reasoning efficiency of the system is also lower.
论文还详细介绍了数控刀具事实库、规则库以及数控刀具选配系统推理机的设计方法，并建立了基于专家系统的数控刀具选配系统模型。
This paper also introduces the design methods of fact base, rule base and reasoning machine design method of NC tool selection system, and establishes NC tool selection model based on expert system.
设计一种新型混合模糊神经推理系统，该系统仅从期望输入输出数据集即可达到获取知识、确定模糊初始规则基的目的。
A novel hybrid neural fuzzy inference system is presented. Only based on the desired input output data pairs, are the knowledge acquisition and initial fuzzy rule sets available.
该系统采用状态映照平面初始化方法、未知模式标定技术和在线识别技术，并结合知识库和规则推理的运用，有效地实现设备状态的分类。
The system adopts the techniques of initialization of state mapping plane, calibration of unknown pattern and on-line identification and this makes plant condition clustering efficiently.
基于专家系统工具，开发了TBM状态监测和故障诊断专家系统，阐述了系统的结构原理、推理规则、目标实现过程。
Situation monitoring and trouble diagnosis expert system for TBM is developed. The structure principle, inference rule and goal attaining process are described.
通过对基于规则、模型与案例推理的分析，给出了基于混合推理策略的半智能CAFD系统总体结构。
Through the analysis on ruled based and model based and case based reasoning, an overall structure of semi intelligent CAFD system based on mixed reasoning strategy is presented.
通过对基于规则、模型与案例推理的分析，给出了基于混合推理策略的半智能CAFD系统总体结构。
Through the analysis on ruled based and model based and case based reasoning, an overall structure of semi intelligent CAFD system based on mixed reasoning strategy is presented.
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