Knowledge Representation and Fuzzy Reasoning of an Agricultural Expert System

The design scheme of an agricultural expert system based on longan and cauliflower planting techniques is presented. Using an object-oriented design and a combination of the techniques in multimedia, database, expert system and artificial intelligence, an in-depth analysis and summary are made of the knowledge features of the agricultural multimedia expert system and data models involved. According to the practical problems in agricultural field, the architectures and functions of the system are designed, and some design ideas about the hybrid knowledge representation and fuzzy reasoning are proposed.

A DEVELOPING TOOL FOR THE EXPERT SYSTEM IN TECHNOLOGY DESIGN AND EXPERT SYSTEM FOR COCOON COOKING

This paper demonstrates the general character of some technology designing processes through their analysisand introduces a developing tool for the expert system in technology design.With this tool a particular domain ex-pert can directly establish a knowledge base so as to form a practical expert system,and thus enhanca correctness ofknowledge experssion and the developing efficiency of the expert system.It also discusses in detail the mech-anism of reasoning,interpreting and knowledge obtaining.The knowledge base consists of three parts:classifyingrules,essential data,and regulating rules.It can be formed by means of the expert dialouge and edition.In its ap-plication,the knowledge base can constantly accumulate successful experience to achieve itsself-study function.The paper shows the way to describe the knowledge in a particular domain and the process of applying this tool ina particular domain. The tool is written in Turb-Prolog language,And an expert system for cocoon cooking isprovided.

Knowledge-Based Systems for the Assessment and Management of Bridge Structures: A Review

It is becoming an important social problem to make maintenance and rehabilitation of existing infrastructures such as bridges, buildings, etc. in the world. The kernel of such structure management is to develop a method of safety assessment on items which include remaining life and load carrying capacity. The purpose of this paper is to summarize the finding of up-to-date research articles concerning the application of knowledge-based systems to assessment and management of structures and to illustrate the potential of such systems in the structural engineering. In here, knowledge-based systems include knowledge-based expert systems incorporation with artificial neural networks, fuzzy reasoning and genetic or immune algorithms. Specifically, two modern bridge management systems (BMS’s) are presented in the paper. The first is a BMS to assess the performance and derive optimal strategies for inspection and maintenance of concrete bridge structures using reliability based and knowledge-based systems. The second is the concrete bridge rating expert system (J-BMS BREX) to evaluate the performance of existing bridges by incorporating with artificial neural networks and fuzzy reasoning.

Experts' Knowledge Fusion in Model-Based Diagnosis Based on Bayes Networks

In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that "if component m 1 is faulty, then component m 2 may be faulty too". How can we use this experts’ knowledge to aid the diagnosis? Based on Kohlas’s probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts’ knowledge.

Geological Analogy Expert System of Oil-Generating Depressions

The geologic analogy expert system of oil-generating depressions(GAESOD)constructed on IBM386 by using GCLISP language is a tool-type expert system for geologic analogy.GAESOD consists ofeight parts:(1)illustrating module of system;(2)general controlling module;(3)knowledge base;(4)rea-soning module;(5 )data base;(6)explanation module;(7)gaining and managing module of knowledge;(8)managing module of data base.There are 36 known models of oil—generating depressions of the eastern partand me continental shelf of China in the knowledge base.Three values,such as resemblance coefficient,cer-tainty factor and fine-poor coefficient,will be acquired if this system is applied to any two oil-generatingdepressions.Finally,GAESOD are applied to the analysis of some data from Xichang depression,Hepubasin and the conclusions from this system are consistent with the results from geologic experts.

Study on the System Design of Multiple Expert Systems Integrated Decision Support System

There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers’ ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.

Reasoning Disaster Chains with Bayesian Network Estimated Under Expert Prior Knowledge

With the acceleration of global climate change and urbanization,disaster chains are always connected to artificial systems like critical infrastructure.The complexity and uncertainty of the disaster chain development process and the severity of the consequences have brought great challenges to emergency decision makers.The Bayesian network(BN)was applied in this study to reason about disaster chain scenarios to support the choice of appropriate response strategies.To capture the interacting relationships among different factors,a scenario representation model of disaster chains was developed,followed by the determination of the BN structure.In deriving the conditional probability tables of the BN model,we found that,due to the lack of data and the significant uncertainty of disaster chains,parameter learning methodologies based on data or expert knowledge alone are insufficient.By integrating both sample data and expert knowledge with the maximum entropy principle,we proposed a parameter estimation algorithm under expert prior knowledge(PEUK).Taking the rainstorm disaster chain as an example,we demonstrated the superiority of the PEUK-built BN model over the traditional maximum a posterior(MAP)algorithm and the direct expert opinion elicitation method.The results also demonstrate the potential of our BN scenario reasoning paradigm to assist real-world disaster decisions.

基于证据推理算法的网络安全评估

针对目前网络安全评估方法在同时处理各种类型信息时精度不高等问题,提出了一种新的基于证据推理算法的网络安全评估方法.首先选取指标建立多层次的网络安全评估框架.其次,通过专家知识确定各指标的权重、评估等级和参考值,并以证据推理算法融合出来的安全态势评估值为基础,确定最终网络安全评估等级.最后,通过实验验证了该方法可以得出一个合理的评估结果,具有可行性和有效性.

基于专家系统的工作流管理系统模型研究

阐述了专家系统在工作流管理中的应用方法 ,构建了基于专家系统的工作流管理系统的总体模型 ,论述了各功能模块的组成和作用 ,并讨论了系统的执行过程。在此基础上 ,进一步讨论了实现系统的若干关键技术 ,如知识表示方法、推理机制。

基于模糊专家系统的评估诊断方法

针对设备故障诊断中存在的不确定性问题,提出一种将模糊逻辑和专家系统结合的评估诊断方法·模糊专家系统中采用模糊产生式规则表示知识,通过采用模糊匹配的不确定性推理方法进行,并采用以置信度高低为标准的冲突消解策略来实现基于知识的诊断方法·文中介绍了专家系统功能组成和实现方法,同时在电力变压器的气相色谱分析故障诊断方法中应用了该模糊专家系统·通过现场近百次实际诊断,准确率可以达到95 7%,验证了将模糊专家系统应用到变压器的故障诊断中是可行的·

作物知识模型构建方法的研究

为了提高作物研究领域专家系统知识的数量与质量,在分析知识模型研究现状的基础上,结合作物的生育特点,提出了作物知识模型建立的基本依据是作物生育时间和农艺技术措施,并依此建立由浅知识模型和深知识模型所组成的油菜三维知识模型.同时对该知识模型的知识表示和模糊推理进行了描述.该知识模型具有一定的通用性.

面向对象技术在专家系统中的应用研究

本文研究面向对象技术在专家系统开发过程中的应用方法。首先针对专家系统开发各阶段的特点，提出了采用面向对象技术进行分析和设计的方法，分析了此方法的特点。然后，把所提出的方法应用于制造企业生产经营大纲决策支持系统中专家系统的开发，并讨论了系统的软件实现技术。实际应用结果表明，此方法能满足实际问题的需要，是实用的，且是十分有效的。

一个人物关系问答的专家系统

在分析专家系统现有理论技术的基础上,采用自然语言问答的人机交互方式,搭建了《人物关系问答系统》,对专家系统现存的问题进行了有益的探索.测试结果表明,该系统知识完备,表示方法及组织方法适当,求解问题质量高,人机交互便利,效率高,可维护性好,解释能力强.

一种基于关系数据库的知识表示和推理方法

获得一种具有广泛的知识表示方法和灵活高效的推理逻辑是专家系统研究中一直追求的一个目标。将日益发展成熟的关系数据库技术引入专家系统,论述了一种基于关系数据库的知识表示方法和推理逻辑,利用关系数据库几乎不受限制的字段个数和丰富的字段类型来表示专家知识和组织推理逻辑,达到了知识表示的广泛性和逻辑推理的高效性。这一方法可广泛应用于各领域的专家系统,在中医专家系统的实例中,取得了令人满意的效果。

基于启发式规则推理的多媒体农业专家系统开发平台的开发与研究

阐述了多媒体农业专家系统开发平台的系统目标、系统分析及系统实现的关键技术,提出了一种实现启发式规则推理的知识表示方法。

地区电网智能报警系统的构建

智能报警系统根据告警信号的重要性对其进行了分类处理和专家推理。采用实用化的模糊匹配方法,实现了告警信号与告警知识库的自动关联。通过单事件推理和多事件推理方法,根据知识库中的逻辑对报警信息进行推理判断,对电网正常运行、事故发生前、事故发生后的报警信息分别进行处理并主动提示处理方案。

飞机航电设备综合智能故障诊断专家系统研究

目前,智能诊断方法主要有基于规则推理、模糊模型和案例等诊断方法。在分析了上述方法的特征和局限性的基础上,取长补短,提出了综合智能故障诊断方法,通过综合推理策略及统一协调机制,提高诊断系统的故障诊断能力和诊断效率。说明了专家系统综合知识库的建立、综合推理机及软件设计的实现等技术。

加工工艺专家系统实现方法综述

专家系统应用于加工工艺领域里即加工工艺专家系统,为解决复杂的工艺设计问题提供了有利条件。首先阐述了加工工艺的基本概念和构建加工工艺专家系统的意义;然后从知识库、推理机两方面对构建加工工艺专家系统的方法及过程进行了分析总结。其中,从知识获取、知识表示阐述了建立知识库的不同方法及其优缺点;总结了通过采用正向推理、反向推理、正反结合推理、基于实例推理、基于规则推理、基于实例规则集成推理等不同推理策略实现推理机方法及其优缺点;最后指出了构建加工工艺专家系统尚存在的问题,给出展望。

基于.NET的对虾病害防治专家系统的设计与实现

针对我国对虾养殖存在的问题,采用ASP.NET技术设计实现了基于B/S结构的对虾增养殖及病害防治专家系统。该系统运用多种知识表示方法将对虾养殖、疾病诊断与防治等经验性、科普性知识进行了集成表达,采用基于规则的模糊化混合推理策略,实现了对虾养殖的咨询与决策、疾病诊断与防治、专家会诊及网上学习等功能。经实践验证和专家评测,该系统界面友好,操作简单实用,维护方便等特点,具有一定的推广价值。

基于故障树的梭式窑故障诊断专家系统

为实现对梭式窑运行异常特别是燃烧异常的故障检测和定位,研究并设计了一种基于故障树的故障诊断专家系统。首先给出梭式窑故障诊断专家系统的形式化定义,进而详细分析并设计了专家系统的各个组成部分;最后重点介绍使用故障树来设计知识库的原理与方法,以及使用故障树来进行故障诊断推理的算法。工程实践表明,该系统知识模型适应性好,使用简单方便,故障诊断结果可靠稳定。