基于置信规则库的飞控系统故障诊断

针对传统飞控系统故障诊断中存在的因引入专家知识引起的主观偏差问题和使用数据驱动方法因数据量不足导致的过拟合问题,提出了基于置信规则库推理的飞控系统故障诊断。根据已有故障知识构建飞控系统故障诊断置信规则库,利用测试过程中获得的故障数据,以数值样本优化学习模型对置信规则库参数进行训练。实例表明,经少量样本训练后的置信规则库可以很好地解决初始置信规则库参数存在主观偏差的问题,经实验证明该方法能够实现高效可靠的飞控系统故障诊断。     

初中几何专家系统中的知识获取及实现

描述了初中几何专家系统中知识获取及实现的一般过程,指出了知识获取及实现中的难点和重点。由于研究问题的复杂性,专家系统规则库中规则量往往十分庞大,这给规则库的管理和维护带来很大不便。专家系统知识库的冗余性是影响系统运行效率和知识库维护的一个重要方面,针对一个具体的专家系统——平面几何智能解题系统,分析了关于知识库规则生成时效率低的问题,然后利用基于粗糙集的约简理论来消除和减少规则库的冗余,使得系统规则库中的规则精炼、简洁,易于维护,同时大大提高了系统的效率。     

初中几何专家系统中的知识获取及实现

描述了初中几何专家系统中知识获取及实现的一般过程,指出了知识获取及实现中的难点和重点.由于研究问题的复杂性,专家系统规则库中规则量往往十分庞大,这给规则库的管理和维护带来很大不便.专家系统知识库的冗余性是影响系统运行效率和知识库维护的一个重要方面,针对一个具体的专家系统--平面几何智能解题系统,分析了关于知识库规则生成时效率低的问题,然后利用基于粗糙集的约简理论来消除和减少规则库的冗余,使得系统规则库中的规则精炼、简洁,易于维护,同时大大提高了系统的效率.     

基于规则的UML设计模型的一致性检验

统一建模语言(UML)是业界公认的主流面向对象建模语言,为系统开发提供了丰富的建模元素。由于UML不同建模元素之间缺乏准确定义的关系,因此UML模型往往会出现不一致性问题。针对该问题,提出了一种基于规则的检验方法。该方法把UML设计模型和一致性条件分别映射为规则系统的事实库和规则库,如果事实库与规则库不匹配,则表示设计模型中存在不一致性。我们使用自主开发的一种“面向对象-规则语言系统”作为检验一致性的规则系统,它集成了面向对象语言和规则语言两种范型,有利于统一使用C++语言来设计并实现一致性检验工具,提高一致性检验效率。     

虚拟训练系统中过程仿真实现方法研究

以装备操作过程为研究对象,通过基于知识的方法建立操作作业模型,采用数据库技术建立规则库,使用临时规则库存储操作作业,实现了虚拟训练系统中过程仿真,解决了过程仿真中并行操作问题,节约了系统开销时间,使过程控制同应用程序分离,提高了应用程序的通用性.     

规则库的冗余测试

规则冗余会引起专家系统效率低下、增加维护代价等不利后果,在专家系统中,保持规则库的精练和简洁,避免规则冗余是规则库组织和管理中必须解决的首要问题。概述了冗余规则的分类,并利用这些规则通过算法对某农业专家系统进行测试,发现此知识库存在一定程度的冗余性,但事实证明要完全控制规则的冗余性是不可判定的。     

钻井液设计专家系统规则库的检测算法

钻井液设计专家系统规则库的规模随着规则的更新与日俱增,对规则库的维护工作变得日益重要。针对规则库的从属、冗余、环路和冲突等问题提出一种检测算法。引入有向超图来表示规则库中的规则;用邻接矩阵表示该有向超图,并计算出它的可达矩阵和总可达矩阵;用总可达矩阵对规则库进行检测,找出规则库中存在的问题。实验表明,与已有的检测算法相比,该算法能够有效地检测出规则库中存在的问题,同时构建的邻接矩阵规模较小,在保证算法简洁的基础上提高了效率。     

作战实验规则库管理系统设计与实现

针对作战仿真系统的规则建设标准不一,规则数据难以重用的问题,提出一种通用的作战实验规则库管理系统架构。首先提出了基于实体、行为、裁决三要素的规则的分类方法以及基于知识元的规则形式化描述方法,对规则的管理和描述方式进行统一,然后选取了Apache服务器、MySQL数据库、PHP开发语言作为作战实验规则库管理系统的构建技术,使用Ztree插件实现了用户界面的规则导航功能,最后从系统需求分析、功能模块设计、规则库设计等方面介绍了管理系统的设计过程。     

基于改进规则激活率的扩展置信规则库推理方法

数据驱动的扩展置信规则库系统,是在传统置信规则库的基础上利用关系数据来生成规则,使用该方法构建规则库简单有效。然而,该方法激活的规则存在不一致与不完整,并且该方法无法处理零激活的输入。鉴于此,本文提出基于改进规则激活率的扩展置信规则库方法,通过高斯核改进个体匹配度计算方法,权衡激活规则的一致性与完整性,并利用k近邻思想解决规则零激活问题。最后,本文选取非线性函数拟合实验和输油管道检漏实验来检验所提方法的效率和准确度。实验结果表明该方法既保证了扩展置信规则库系统的推理效率,也提高了推理结果的精度。     

应急响应系统的规则冗余检测技术研究*

在应急响应系统（ERS）中,规则及规则推理用于确定应急事件的响应级别。当系统的规则库增加规则时,会出现冗余的规则,冗余规则的存在导致响应级别的判断不准确,影响推理的效率和准确性。针对该问题,提出一种规则的冗余检测方法,使规则库中的规则始终保持无冗余状态;同时,给出了冗余规则的处理方法。最后给出该算法的一个应用实例,结果表明该算法能快速检测出冗余规则,有效降低规则数目。     

A neural-network model for learning domain rules based on itsactivation function characteristics

A challenging problem in machine learning is to discover the domain rules from a limited number of instances. In a large complex domain, it is often the case that the rules learned by the computer are at most approximate. To address this problem, this paper describes the CFNet which bases its activation function on the certainty factor (CF) model of expert systems. A new analysis on the computational complexity of rule learning in general is provided. A further analysis shows how this complexity can be reduced to a point where the domain rules can be accurately learned by capitalizing on the activation function characteristics of the CFNet. The claimed capability is adequately supported by empirical evaluations and comparisons with related systems.     

Size reduction by interpolation in fuzzy rule bases

Fuzzy control is at present still the most important area of real applications for fuzzy theory. It is a generalized form of expert control using fuzzy sets in the definition of vague/linguistic predicates, modeling a system by If...then rules. In the classical approaches it is necessary that observations on the actual state of the system partly match (fire) one or several rules in the model (fired rules), and the conclusion is calculated by the evaluation of the degrees of matching and the fired rules. Interpolation helps reduce the complexity as it allows rule bases with gaps. Various interpolation approaches are shown. It is proposed that dense rule bases should be reduced so that only the minimal necessary number of rules remain still containing the essential information in the original base, and all other rules are replaced by the interpolation algorithm that however can recover them with a certain accuracy prescribed before reduction. The interpolation method used for demonstration is the Lagrange method supplying the best fitting minimal degree polynomial. The paper concentrates on the reduction technique that is rather independent from the style of the interpolation model, but cannot be given in the form of a tractable algorithm. An example is shown to illustrate possible results and difficulties with the method.     

基于SOA的业务规则代理研究

针对业务规则领域存在的问题,分析规则引擎主要的实现技术与规范以及基于SOA规则引擎的优越性,提出基于SOA的规则引擎代理。该结构能屏蔽不同业务规则引擎之间的异构性,向客户端提供统一的Web服务接口来执行不同规则引擎的规则。给出应用于移动公司的具体实例。     

ECA规则在工作流管理系统中的应用

针对工作流管理系统的实现复杂性及模型可靠性的验证问题,提出了一种结合工作流网和ECA规则来创建工作流管理系统的方法。这种基于ECA规则的工作流描述和执行机制较好地实现了工作流网模型的语义描述和控制的统一。通过建立基于ECA规则的工作流描述表,将ECA 规则引入到工作流路由机制中,灵活地控制了工作流的流程。通过事件触发和消息处理机制,工作流描述表处理可以被实际系统加以执行和控制。     

Clustering rule bases using ontology-based similarity measures

Rules are increasingly becoming an important form of knowledge representation on the Semantic Web. There are currently few methods that can ensure that the acquisition and management of rules can scale to the size of the Web. We previously developed methods to help manage large rule bases using syntactical analyses of rules. This approach did not incorporate semantics. As a result, rule categorization based on syntactic features may not be effective. In this paper, we present a novel approach for grouping rules based on whether the rule elements share relationships within a domain ontology. We have developed our method for rules specified in the Semantic Web Rule Language (SWRL), which is based on the Web Ontology Language (OWL) and shares its formal underpinnings. Our method uses vector space modeling of rule atoms and an ontology-based semantic similarity measure. We apply a clustering method to detect rule relatedness, and we use a statistical model selection method to find the optimal number of clusters within a rule base. Using three different SWRL rule bases, we evaluated the results of our semantic clustering method against those of our syntactic approach. We have found that our new approach creates clusters that better match the rule bases’ logical structures. Semantic clustering of rule bases may help users to more rapidly comprehend, acquire, and manage the growing numbers of rules on the Semantic Web.     

Decomposition of a fuzzy controller based on the inference break-up method

A concept called the decomposition of multivariable control rules is presented. Fuzzy control is the application of the compositional rule of inference and it is shown how the inference of the rule base with complex rules can be reduced to the inference of a number of rule bases with simple rules. A fuzzy logic based controller is applied to a simple magnetic suspension system. The controller has proportional, integral and derivative separate parts which are tuned independently. This means that all parts have their own rule bases. By testing it was found that the fuzzy PID controller gives better performance over a typical operational range then a traditional linear PID controller. The magnetic suspension system and the contact-less optical position measurement system have been developed and applied for the comparative analysis of the real-time conventional PID control and the fuzzy control.     

信息系统数据清洗、规则提取的矩阵算法

本文在等价矩阵概念的基础上，分析了粗糙集知识系统中等价划分与等价矩阵的关系，采用等价矩阵来表示粗糙集的等价关系，提出了一种对数据库知识系统进行数据清洗、从中提取决策规则的矩阵算法，并分析了该算法的计算复杂性．该算法具有规则提取的工程实用性，主要优点在于能够获得信息系统中所有有价值的决策规则．文中通过实例表明了这种算法的有效性．     

Strategy Construction in the Higher-Order Framework of TL

When viewed from a strategic perspective, a labeled rule base in a rewriting system can be seen as a restricted form of strategic expression (e.g., a collection of rules strictly composed using the left-biased choice combinator). This paper describes higher-order mechanisms capable of dynamically constructing strategic expressions that are similar to rule bases. One notable difference between these strategic expressions and rule bases is that strategic expressions can be constructed using arbitrary binary combinators (e.g., left-biased choice, right-biased choice, sequential composition, or user defined). Furthermore, the data used in these strategic expressions can be obtained through term traversals.A higher-order strategic programming framework called TL is described. In TL it is possible to dynamically construct strategic expression of the kind mentioned in the previous paragraph. A demonstration follows showing how the higher-order constructs available in TL can be used to solve several problems common to the area of program transformation.     

Simplification of a fuzzy mechanism with rule combination

 In this paper, a systematic approach to reduce the complexity of a fuzzy controller with the rule combination of a fuzzy rule base is presented. The complexity of a fuzzy controller is defined to be the computation load in this work. The proposed rule combination approach can be applied to the fuzzy mechanisms with product–sum and min–max inferences. With the input membership functions indexed in sequence for each input variable, the n-dimensional fuzzy rule table is represented as vectors so that the combination of the fuzzy rule base is realizable. Then the adjacent fuzzy rules with the same output consequent are combined to have smaller size of fuzzy rule base. The fuzzy mechanism with the combined rule table is shown to have the same output with the original fuzzy mechanism (without rule combination). Thus, in many applications, the rule combination approach presented in this paper can be used to reduce the complexity of the fuzzy mechanism without degrading the performances. Moreover, the Don't Care fuzzy rules are defined and it is indicated that the number of the necessary fuzzy rules might be decreased when the Don't Care fuzzy rules are taken into consideration. Further, the properties of the simplification approach for the fuzzy rule base of the fuzzy mechanism are discussed.