产生式规则专家系统的原理与实现

不确定的知识表示与知识推理是专家系统研究和开发的难点。本文利用“目标驱动”方法中控制模块、规则库和事实数据库的操作原理，使用SQL Server2000和Delphi 6．0作为开发平台，通过数据格式和算法的设计构造并实现了一个产生式规则专家系统。该系统实现了不确定性知识表示和知识推理的计算机化，用户只需要为系统提供足够的已知数据，就可以获得专家水平的结论。     

证据理论在不确定性推理中的应用研究*

利用证据理论中的基本概率分配函数、信任函数和似然函数来描述和处理知识的不确定性。提出一个特殊的概率分配函数和新的组合规则,并以其为基础建立一个不确定性推理模型。实例证明该模型能有效地度量最终结论的不确定性。     

不确定模式集成中领域知识应用模型的研究

结合关系模型、产生式规则和自主计算三者的优点,提出了一个任务驱动的自主推理的动态领域知识应用模型。在该模型中,将领域知识按需要进行聚类,根据任务进行规则映射和推理模块中不同处理器的选择,运用证据组合方法合并各处理阶段的不确定度,采用基于自适应控制策略的自主计算技术进行知识推理。推理结果被应用到不确定模式集成模型的其他模块中,辅助解决模式集成中存在的不确定性问题。经实例验证该模型是可行的。     

基于确定因子的不确定性推理的仿真实现

针对传统的基于确定因子的不确定性推理模型在实际应用中出现的几个问题,提出了一种新型的以数理统计理论为基础、通过采用计算机模拟的方法来实现不确定性推理模型中相关参数的算法模型,并对基于确定因子的不确定性推理模型的相关知识作了详细叙述。根据所给出的算法模型,以地震预报专家系统中某条知识表示的规则强度CF的值的得出为例,完成了对CF的模拟,详细阐述了方法的实现过程并对模拟出的值的可信程度进行了检验,结果证明模拟技术为人工智能研究领域的不确定性推理的应用提供一种新的方法。     

一种扩展式CRFs的短语情感倾向性分析方法研究

短语情感倾向性分析是文本情感分析的重要研究内容。该文将短语情感倾向性分析问题视作序列标注问题,利用条件随机场模型实现短语的情感倾向性判断。条件随机场模型是利用序列特征处理序列标注问题的经典方法,然而现有条件随机场模型无法将词语的情感倾向性分析与短语的情感倾向性分析相结合,从而造成准确率不高。因此,该文提出一种扩展式条件随机场模型YACRFs。该模型在链式条件随机场模型的基础上进行扩充,将词语情感倾向性分析与短语情感倾向性分析有效地结合起来,引入了情感词汇、短语规则模板以及词性等特征。与传统的规则方法和统计分类方法进行对比实验,该文提出方法取得了最高准确率81.07%。进一步地,在应用于句子情感倾向性分析的实验中得到了94.30%的准确率。实验结果表明,该文所提出的YACRFs模型能够显著提高短语情感倾向性判断结果的准确率。     

无线传感网数据不确定性及其分层多Agent调和策略

针对无线传感网数据不确定性处理有效性策略研究,分析了传感数据不确定的多样性和层次性,设计了sensor Agent、cluster and analyzer Agent和sink and decision-maker Agent三类Agent,探讨了传感数据不确定性类与多智能Agent分层对应关系。具体定义了Agent的局部不确定数据处理和通信两种调和组成模块,以及无线传感网与粗糙集技术的智能特性组合,进而提出了传感不确定性分层多智能Agent调和模型。最后,给出了相应实现算法及实例分析,结果表明该智能模型分层调和机制具有化解各类复杂传感数据不确定性的灵活性与实用性。     

DS证据理论下融合隐式与显式特征的共谋攻击识别推理模型

现有的攻击识别模型大多未能较好地解决共谋攻击对电子商务信任评价机制产生的威胁。为此,结合国内C2C电子商务的特点,以共谋攻击中的商品为识别对象,融合隐式和显式用户行为特征以及与交易和买家相关的复合特征,并根据DS证据理论处理不确定问题的优点,提出一种DS证据理论下的共谋攻击识别推理模型。在某电商平台真实共谋攻击数据上的实验结果表明,该推理模型能够识别共谋攻击,提取的攻击识别特征可反映用户真实行为,有效区分攻击和合法交易所涉及的商品。     

一种不确定性条件下的自主式知识学习模型

在没有领域先验知识条件下的不确定知识主动式学习是机器学习领域中的一个难题.通过研究决策表和决策规则的不确定性,建立基于粗集表示、度量和处理不确定性信息和知识的理论,并且结合Skowron的缺省规则获取算法,提出一种不确定性条件下的数据自主式学习模型和方法,以解决这一问题.通过仿真实验,验证了该自主式学习方法的有效性.     

基于数据库的燃煤锅炉事故诊断专家系统的设计与实现

采用MS SQL Server7．0设计知识库，Visual Basic 6．0编程实现了燃煤锅炉事故诊断专家系统。本系统知识表示采用了基于概率逻辑的产生式规则形式，并用数据库的方法存储管理知识库。推理机采用规则值的方法，并应用主观Bayes理论建立了不确定性推理模型。实现了一种较为理想的不精确推理。     

基于免疫遗传的状态转移分析模型

为解决现有入侵检测技术对于新类型攻击或隐蔽攻击识别率很低的问题，提出了一个免疫遗传模型来重新构造状态转移分析检测方法。在该模型中使用了由状态链和行为链组成的双链基因模式来表示系统的状态转移，并使用STAT系统的原有检测规则来构造初始的专家DNA疫苗库。试验证明了该模型的有效性。     

Milling Fault Detection Method Based on Fault Tree Analysis and Hierarchical Belief Rule Base

Expert knowledge is the key to modeling milling fault detection systems based on the belief rule base. The construction of an initial expert knowledge base seriously affects the accuracy and interpretability of the milling fault detection model. However, due to the complexity of the milling system structure and the uncertainty of the milling failure index, it is often impossible to construct model expert knowledge effectively. Therefore, a milling system fault detection method based on fault tree analysis and hierarchical BRB (FTBRB) is proposed. Firstly, the proposed method uses a fault tree and hierarchical BRB modeling. Through fault tree analysis (FTA), the logical correspondence between FTA and BRB is sorted out. This can effectively embed the FTA mechanism into the BRB expert knowledge base. The hierarchical BRB model is used to solve the problem of excessive indexes and avoid combinatorial explosion. Secondly, evidence reasoning (ER) is used to ensure the transparency of the model reasoning process. Thirdly, the projection covariance matrix adaptation evolutionary strategies (P-CMA-ES) is used to optimize the model. Finally, this paper verifies the validity model and the method's feasibility techniques for milling data sets.     

故障诊断专家系统及其发展

文章对主要的故障诊断专家系统进行了系统的归纳和分类,主要关注故障诊断专家系统在军事领域的应用;重点讨论了基于规则的诊断专家系统、基于模型的诊断专家系统、基于人工神经网络的诊断专家系统、基于模糊推理的诊断专家系统和基于事例的诊断专家系统的技术要点、发展现状、优缺点及其在军事方面的应用;最后,对该学科的发展做出了预测,指出基于多种模型结合的诊断专家系统、分布式诊断专家系统、实时诊断专家系统是今后的发展方向。     

基于Agent的专家系统推理模型

针对传统专家系统推理模型结构在知识获取方面适应性差的现状,从系统科学的视角,运用复杂适应系统理论,对传统专家系统的结构及运行机制进行了改进.引入Agent来模拟人脑中的神经元,用来承载专家系统中相互作用的知识,然后,基于Multi-Agent之间的相互作用来构建复杂适应的专家系统推理模型.从而,将专家系统中的知识获取机制、知识库、推理机三者统一于由Multi-Agent进行相互作用的复杂适应系统之中.通过设计体育赛事申办决策专家系统的原型,进行了专家系统推理模型的验证.原型运行结果表明:基于Multi-Agent的专家系统推理模型结构能够有效地提高专家系统知识获取的适应性.这为研究更加接近人脑智能的专家系统提供了崭新的研究思路.     

基于知识的航电设备故障诊断专家系统

为了解决航电设备故障难以诊断的问题,设计一个基于知识的航电设备故障诊断专家系统。该系统中的知识表示形式及与之相配合的基于确定性理论模型的不确定性推理方法,以及基于示例的推理方法可以实现航电设备的故障推理和诊断,其规则的可信度可达到理想的程度。     

基于Ontology的专家系统研究

针对当前专家系统领域知识语义表示不精确及推理效率低的问题,提出一种基于Ontology的专家系统框架。根据规则结构建立规则模式Ontology和动作Ontology,将用户推理条件作为模式子Ontology,设计出基于名称和实例的相似度计算及Clips推理机制的专家系统推理算法。结合高性能切削加工应用背景给出一个应用实例,应用结果表明,该系统能够明显提高推理效率和推理结果的语义表达。     

基于置信规则库的工业控制系统安全状态评估

当前工业控制系统存在严重安全问题,针对现有工业控制系统安全状态评估模型存在的不足,提出一种基于置信规则库(BRB)专家系统的工业控制系统安全状态评估方法.该方法首先利用置信规则库专家系统将工业控制系统中定性知识与定量监测数据相结合.然后采用证据推理(ER)算法进行知识推理,并对所建立的BRB模型初始参数进行优化.最后以...     

Ecological applications using a novel expert system shell

Much of the information used by ecologists in modelling and decision making is imprecise. The imprecision arises both from data that are inexact or incomplete and from the use of ecological principles that are sometimes less than fully reliable and may be conflicting. Nevertheless, expert ecologists are able to construct usable models and make decisions that are used to manage and control ecological resources. This paper describes a unique expert system shell, developed in conjunction with user ecologists, which incorporates features enabling ecologists to represent knowledge and uncertainty in their expert systems in a way that is natural and appropriate. The reasoning mechanism was similarly developed in conjunction with user ecologists. It produces solutions to a class of expert level problems along with explanatory mechanisms and an appropriate analysis of the reasoning process. Three expert systems have been constructed by ecologists using this expert system shell. This enabled the shell designers to evaluate features for inclusion in the shell. The successful use of the shell by the ecologists has shown that significant economies arise when expert system shell design is tailored to use by a specific class of experts, in this case ecologists.     

基于MAS的航空机务维修差错预警专家系统

机务维修是关系到民用航空安全和效益的重要因素之一,是飞行安全的基础,因此迫切需要建立航空机务维修差错预警专家系统。采用Agent技术作为低层支撑技术,将基于规则的不确定性推理和基于案例推理的预警方法引入航空机务维修差错预警领域,给出了总体结构的设计以及关键技术的实现,从而为航空机务维修差错预警提供了一种新的思路和方法。     

A fuzzy expert system shell using both exact and inexact reasoning

This paper presents a comprehensive expert system shell which can deal with both exact and inexact reasoning. A prototype of this proposed shell, code named as SYSTEM Z-IIe, has been implemented successfully. It is a rule-based system which employs fuzzy logic and numbers for its reasoning. Two basic inexact concepts, fuzziness and uncertainty, are both used and distinct from each other clearly in the system. Moreover, these two concepts have been built into two levels for inexact reasoning, i.e. the level of the rules and facts, and the level of the values of the objects of these rules and facts. Other features of Z-IIe include multiple fuzzy propositions in rules and dual fact input mechanisms. It also allows any combinations of fuzzy and normal terms and uncertainties. Fuzzy numeric comparison logic control is also available for the rules and facts. Its natural language interface which uses English with restricted syntax improves the efficiency of knowledge engineering. Z-IIe is also coupled to a Database Management System for supplying facts from existing databases if appropriate. All these features can be combined to build very powerful expert systems and are illustrated by an example.     

A reasoning method for a ship design expert system

Abstract: The ship design process is a highly data‐oriented, dynamic, iterative and multi‐stage algorithm. It utilizes multiple abstraction levels and concurrent engineering techniques. Specialized techniques for knowledge acquisition, knowledge representation and reasoning must be developed to solve these problems for a ship design expert system. Consequently, very few attempts have been made to model the ship design process using an expert system approach. The current work investigates a knowledge representation–reasoning technique for such a purpose. A knowledge‐based conceptual design was developed by utilizing a prototype approach and hierarchical decompositioning. An expert system program called ALDES (accommodation layout design expert system) was developed by using the CLIPS expert system shell and an object‐oriented user interface. The reasoning and knowledge representation methods of ALDES are explained in the paper. An application of the method is given for the general arrangement design of a containership.