Expert systems based on LCTV AND/OR logic

A problem in expert systems is typically represented by an AND/OR graph. A set of spatial light modulators which can perform AND and OR logic operations can directly be applied to form an optical inference engine. The threshold-dependence logic operations of relatively low contrast and small dynamic range liquid crystal television are explained. The parallel inference architecture operated by liquid crystal televisions is presented.     

Application of Information Technologies and Programming Methods of Embedded Systems for Complex Intellectual Analysis

An information model is outlined, which represents an intelligent system of metallographic analysis in the form of a set of subsystems, the interaction of which ensures the performance of metallographic analysis functions. The structure of the information storage subsystem for metallographic analysis is presented. The deployment model of an intelligent metallographic analysis system is proposed and described. The paper outlines the approach to the presentation of an expert subsystem for metallographic quality control of metals based on a neural network. The process of finding a close precedent in metallographic analysis with reference to a multilayer neural network is described. An intelligent metallographic analysis system is described, which based on proposed information model. A specialized software of an intelligent metallographic analysis system is presented. The functioning results of the developed system for processing images of steel microstructures to determine the steel quantitative parameters is presented.     

血液分析仪专家诊断系统的设计

针对目前血液分析仪无法自动诊断血液疾病的现状,提出了一种应用于血液分析仪的专家诊断系统。本系统在传统专家系统结构的基础上进行了改进,以专家经验、国际血液学复检专家组推荐的复检规则以及临床案例为知识源,利用关系型数据库技术设计出一种产生式树形结构的知识库,并结合Snort规则库中的三维链表数据结构对知识库进行优化,最终完成了血液分析仪专家诊断系统的研制。实验结果：系统诊断的假阳性率为2.7%,假阴性率为3.31‰。结论：本文提出的专家诊断系统具有推理灵活、实时性好的特点。     

Present and future of expert systems in food analysis

This paper presents an overview of the most relevant contributions in the field of expert system (ES) applications in chemical analysis of foods, along with a critical discussion of future, would-be developments. It illustrates the possibilities offered as well as the fact that quality control laboratories should be aware of the power of artificial intelligence that modern computer technology affords. It is worth noting that the applications described are straightforward with a certain versatility and can, therefore, be implemented for other analytes and/or food samples. Special attention is devoted to the promising distributed knowledge-based systems due to their potential advantages over the existing centralized approaches, as inferred from a recent example of application to the on-line monitoring of some key chemical parameters in the course of a food production process. Short and middle term predictions concerning the potential of ES in food analysis are also made.     

计算机辅助针灸诊疗专家系统-ZES及其壳体-KZES

本文论述ZES的功能和开发技术。描述了系统中推理的数学模型及其理论基础,最后阐述了ZES的外壳可用作建造中医专家系统的工具。     

An eigenvalue method on group decision

I.ThePrincipleofGEMInthefollowing,wewi1levaluatenobjectsB,,B1,"-,B,bygroupdecisionsupportsystemGwhichconsistsofmexpertsS,,S,,..',S..Letx',E[I,J](f=1,2'...,mlj=l,2,"',n)betheevaluationvalueofthejthobjectBjestimatedbythei-tllexpertS'.Thelargerxqis,themoreop…     

Health risk assessment for nanoparticles: A case for using expert judgment

Uncertainties in conventional quantitative risk assessment typically relate to values of parameters in risk models. For many environmental contaminants, there is a lack of sufficient information about multiple components of the risk assessment framework. In such cases, the use of default assumptions and extrapolations to fill in the data gaps is a common practice. Nanoparticle risks, however, pose a new form of risk assessment challenge. Besides a lack of data, there is deep scientific uncertainty regarding every aspect of the risk assessment framework: (a) particle characteristics that may affect toxicity; (b) their fate and transport through the environment; (c) the routes of exposure and the metrics by which exposure ought to be measured; (d) the mechanisms of translocation to different parts of the body; and (e) the mechanisms of toxicity and disease. In each of these areas, there are multiple and competing models and hypotheses. These are not merely parametric uncertainties but uncertainties about the choice of the causal mechanisms themselves and the proper model variables to be used, i.e., structural uncertainties. While these uncertainties exist for PM2.5 as well, risk assessment for PM2.5 has avoided dealing with these issues because of a plethora of epidemiological studies. However, such studies don’t exist for the case of nanoparticles. Even if such studies are done in the future, they will be very specific to a particular type of engineered nanoparticle and not generalizable to other nanoparticles. Therefore, risk assessment for nanoparticles will have to deal with the various uncertainties that were avoided in the case of PM2.5. Consequently, uncertainties in estimating risks due to nanoparticle exposures may be characterized as ‘extreme’. This paper proposes a methodology by which risk analysts can cope with such extreme uncertainty. One way to make these problems analytically tractable is to use expert judgment approaches to study the degree of consensus and/or disagreement between experts on different parts of the exposure–response paradigm. This can be done by eliciting judgments from a wide range of experts on different parts of the risk causal chain. We also use examples to illustrate how studying expert consensus/disagreement helps in research prioritization and budget allocation exercises. The expert elicitation can be repeated over the course of several years, over which time, the state of scientific knowledge will also improve and uncertainties may possibly reduce. Results from expert the elicitation exercise can be used by risk managers or managers of funding agencies as a tool for research prioritization.     

Generating beta random rate variables from probabilistic estimates of fireline production times

An extension of probabilistic PERT/CPM is proposed as a framework for soliciting expert opinion to characterize random variables for stochastic treatment in simulation models. By eliciting minimum, modal, ninetieth percentile, and maximum estimates, the distribution of variables with probability density functions of beta form can be explicitly characterized without relying on the traditional, but empirically unverified, assumption of a standard deviation equal to one-sixth of the range. This practical and inexpensive technique is illustrated by application to a wildfire protection planning problem – estimating the time required to produce a given length of fireline by different firefighting resources under diverse conditions. The estimated production times are an essential input to a planning model of initial attack on wildland fires used by the California Department of Forestry and Fire Protection, and provide that agency with useful rules-of-thumb for use in firefighter training.     

GRG在雷达对抗训练水平评估指标权重中的应用

在现代战争中,地对空雷达对抗日趋重要,对于地对空雷达对抗装备训练水平评估成为了亟待解决的问题.开展对地对空雷达对抗训练内容的分析, 构建了地对空雷达对抗训练水平评估指标体系,运用层次分析法确定个体指标权重,再将所有专家的个体指标权重集结为群体指标权重, 根据灰色关联度(GRG)计算各专家的个体指标权重与群体指标权重的接近程度从而确定专家权重,采用了权重自适应调整的方法调整专家权重和群体指标权重,最终确定指标权重.最后,用实例说明了该方法的实用性.     

色谱专家系统的应用和发展

随着科学技术的发展,色谱专家系统作为一种人工智能方法亦在不断发展,并在实际工作中发挥着越来越重要的作用。该文综述了作者的研究小组在色谱专家系统研究方面的进展,重点介绍从研究气相色谱专家系统开始,到应用色谱专家系统的思想,运用气相色谱、液相色谱和毛细管电泳新技术解决石化、环境、疾病诊断、基因分析和药物分析等领域实际问题的工作。引用相关文献64篇。