Railway route planning in Australia

A software company and major travel agent have jointly developed an expert/information retrieval system. The system maps out itineries through Australia's complex rail network. Queries on this subject had previously always been passed to the human expert.     

Contextual fuzzy cognitive map for decision support in geographicinformation systems

Fuzzy cognitive maps or FCMs have been shown to be useful when representing qualitative data. We have shown that these FCM structures can be used to represent quantitative and qualitative data. We illustrate this structure applied to geographic information system (GIS) applications. We illustrate the types of CFCMs we can generate using real census data, human expert knowledge, and quantitative data in the form of maps in a GIS. The goal of this system is to use objects (topographical and conceptual) and their relationships, either supplied by census data or generated by the GIS and to map them as layers in the GIS. Using fuzzy membership functions from experiments with GIS users, we can construct CFCMs for decision support. This will also have significant applications in intelligent servants that are able to assist and interact with the human user     

Constrained unidimensional scaling with application to genomics

A constrained unidimensional scaling model where the objects are required to be placed in a given order on the real line, is studied. A procedure formulated as a least squares problem with nonnegativity is considered to solve this problem. An application to linkage disequilibrium (LD) maps for human genome is presented to demonstrate the proposed model. The LD maps are also constructed for four populations from Hapmap data sets, and analyze some of their similarities.     

What makes expert systems survive over 10 years—empirical evaluation of several engineering applications

This case study analyzes eight expert system applications that have successfully been in industrial use for a long time. We have personally been involved in the development of these applications and are thus in a good position to analyze what is important for a successful application and what kind of mistakes can be made. Since the development of the applications started in 1986–1990 and some of them are still in use we are able to observe what has happened to those applications during their lifetime. Our key observations are related to the scope of the applications, to the trade-off between usability and automation, to the role of human experts in the use and development of expert systems, on the technical solutions used, on aspects of the operation of the expert system and on the similarities between expert systems and information systems. The key findings are expressed as 20 hypotheses for successful expert systems. The support of each application to the hypotheses is discussed.     

专家知识地图的关键技术与设计

专家隐性知识是社会的宝贵财富。开发专家知识地图是有效利用专家知识的重要途径。构建专家知识地图的关键技术包括专家信息的获取、知识地图的体系结构与实现技术。本文给出了通过Web挖掘获取专家基本信息、特长信息和社会网络的算法,以及一个专家知识地图的设计方案。     

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.     

一种基于产生式规则的不确定推理模板模型的研究

该文针对现有不确定推理模型,结合专家知识不确定性在产生式规则系统中的体现,归纳出一种更接近人类专家处理不确定性和方便人们理解与构造实例模型的不确定推理模板模型。该模板模型可作为现有模型的分析模板和新的基于产生式规则的不确定推理模型研究与构造的基本框架模板。该文详细阐述了该模板模型的组成和工作原理,并用它对现有不确定推理模型进行了实例分析;最后,指出该模板模型各组成子模型的研究方向。     

Assessing the accuracy of satellite derived global and national urban maps in Kenya

Ninety percent of projected global urbanization will be concentrated in low income countries. This will have considerable environmental, economic and public health implications for those populations. Objective and efficient methods of delineating urban extent are a cross-sectoral need complicated by a diversity of urban definition rubrics world-wide. Large-area maps of urban extents are becoming increasingly available in the public domain, as are a wide-range of medium spatial resolution satellite imagery. Here we describe the extension of a methodology based on Landsat ETM and Radarsat imagery to the production of a human settlement map of Kenya. This map was then compared with five satellite imagery-derived, global maps of urban extent at Kenya national-level, against an expert opinion coverage for accuracy assessment. The results showed the map produced using medium spatial resolution satellite imagery was of comparable accuracy to the expert opinion coverage. The five global urban maps exhibited a range of inaccuracies, emphasising that care should be taken with use of these maps at national and sub-national scale.     

Using human factor guidelines for developing expert systems

Abstract: Although MIS professionals had predicted that expert systems would improve productivity enormously, and a number of expert system application success stories have been reported, the expert system revolution has not yet happened. Moreover, there have been many cases, less well publicised, where expert systems have failed. Most problems concerning expert systems failure stem from non-technical issues such as cognitive and psychological problems, rather than such purely technical issues as an inference engine and an expert system shell. Here, the major reasons for expert systems failure and the need to consider human factors are discussed. We then propose human factor principles that can help designers handle most of these non-technical problems and many technical ones elegantly, improving the performance and acceptance of expert systems. Finally, some human factor guidelines for expert systems are presented so that these considerations may be incorporated into expert systems development in a clear and comprehensible manner.     

Persuasiveness of expert systems

Expert system advice is not always evaluated by examining its contents. Users can be persuaded by expert system advice because they have certain beliefs about advice given by a computer. The experiment in this paper shows that subjects (n = 84) thought that, given the same argumentation, expert systems are more objective and rational than human advisers. Furthermore, subjects thought a problem was easier when advice on it was said to be given by an expert system while the advice was shown in production rule style. Such beliefs can influence expert system use.     

抗洪抢险专家系统KCExpert的分析与实现

抗洪抢险专家系统KCExpcrt能够实时分析洪水灾情，结合军事运筹学、人工智能技术．通过匹配算法，把不同灾情分派给不同兵种，实现部队在抗洪抢险中最大程度的优化组合。在系统实现过程中，运用专家系统开发工具OKPS，保证知识库和推理机的分离，真正实现抗洪抢险的实时性、可靠性，同时提高系统对突发事件的应急处理能力，尽可能地减少洪灾带来的损失。     

基于MVC模式的桥梁处治专家系统研究

专家系统(Expert system简称ES)是模拟人类专家解决问题的智能程序系统。专家系统的主要特征是有一个巨大的知识库,存储着某个专门领域的知识。在解决问题时,用户为系统提供一些已知数据,然后从系统中获得专家水平的结论[1-2]。目前专家系统已经应用到生活中的各个方面,本文着重研究了专家系统在在役桥梁中的应用,并且给出了模型建立方法、系统设计以及专家系统软件的设计流程[3]。最后将该系统应用到具体的实例中,实验证明在役桥梁专家决策系统具有良好的效果[4]。     

Knowledge base design for law enforcement

This paper describes a project involving the development of an expert system for suspect identification in armed robbery incidents. A prototype of the system, named AREST (Armed Robbery Eidetic Suspect Typing), has been completed and is described. The investigative process can be greatly simplified, expedited, and enhanced by the use of expert systems. An expert system can serve as an aid that handles the preliminary crime analysis and, thus, frees the human officer to concentrate on higher-level analysis worthy of his expertise.     

Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Problems characterized by qualitative uncertainty described by expert judgments can be addressed by the fuzzy logic modeling paradigm, structured within a so-called fuzzy expert system (FES) to handle and propagate the qualitative, linguistic assessments by the experts. Once constructed, the FES model should be verified to make sure that it represents correctly the experts’ knowledge. For FES verification, typically there is not enough data to support and compare directly the expert- and FES-inferred solutions. Thus, there is the necessity to develop indirect methods for determining whether the expert system model provides a proper representation of the expert knowledge. A possible way to proceed is to examine the importance of the different input factors in determining the output of the FES model and to verify whether it is in agreement with the expert conceptualization of the model. In this view, two sensitivity and uncertainty analysis techniques applicable to generic FES models are proposed in this paper with the objective of providing appropriate tools of verification in support of the experts in the FES design phase. To analyze the insights gained by using the proposed techniques, a case study concerning a FES developed in the field of human reliability analysis has been considered.     

A Neural Network Method for Efficient Vegetation Mapping

This article describes the application of a neural network method designed to improve the efficiency of map production from remote sensing data. Specifically, the ARTMAP neural network produces vegetation maps of the Sierra National Forest, in Northern California, using Landsat Thematic Mapper (TM) data. In addition to spectral values, the data set includes terrain and location information for each pixel. The maps produced by ARTMAP are of comparable accuracy to maps produced by a currently used method, which requires expert knowledge of the area as well as extensive manual editing. In fact, once field observations of vegetation classes had been collected for selected sites, ARTMAP took only a few hours to accomplish a mapping task that had previously taken many months. The ARTMAP network features fast online learning, so that the system can be updated incrementally when new field observations arrive, without the need for retraining on the entire data set. In addition to maps that identify lifeform and Calveg species, ARTMAP produces confidence maps, which indicate where errors are most likely to occur and which can, therefore, be used to guide map editing.     

基于Z曲线的SARS冠状病毒特征的研究

刺突（Spike）蛋白是SARS（Severe Acute Respiratory Syndmme）冠状病毒表面最重要的膜蛋白，它通过与被感染细胞的受体结合来作为感染的媒介。受此启发，该文利用Z曲线方法，对S蛋白及SARS受体序列进行探究，捕捉到一种SARS病毒的可视化特征。大量序列比对的结果证明该特征是SARS病毒所特有的。将这种特征图谱应用到SARS病毒的检测中，可以提供一种非标准的、简单、直观的检验方法，能够诊断一些利用标准方法难以判断的SARS病例。由此可见，Z曲线作为一种基因序列的几何学研究途径是一种有效的研究方法。     

USING CAUSAL REASONING IN GAIT ANALYSIS

This paper describes a series of experiments in which expert diagnostic systems were constructed to analyze human pathologic gait. The difference between successive systems is the recognition of the need for both causal reasoning about the process of gait and experiential, associational knowledge that can control causal reasoning. The performance of the first system (DR. GAIT-1), which relies exclusively on associational knowledge, is quite limited. The second system (DR. GAIT-2), because it is based on a qualitative causal model of gait, overcame many of the difficulties faced by the first system, but its ability to diagnose cases is limited by the complexity of causal reasoning. The third system (QUAWDS), which we are currently developing, is an experiment in integrating causal reasoning with associational knowledge so that robust conclusions can be produced efficiently.     

Expert system to control and to design closed loop conveyor systems

A conveyor system is an important part of a manufacturing system. As such, the conveyor system must comply with all the requirements of a modern manufacturing system: high flexibility, high efficiency, and high speed—smart reasoning processes to generate future positions based on a given current status. Because a huge number of figures and numerical manipulatuions are associated with the conveyor systems operations, the traditional numerical control techniques cannot satisfy the requirements to initiate and to control operations. New techniques based on very efficient reasoning processes are required. This article discusses an expert system that consists of a knowledge base and an inference engine that was developed to control a converyor system real-time operation. The computer runs that were performed during this research lead to the conclusion that the developed expert system can be employed to control the conveyor system real time operations very effectively. The developed expert system is considered as a reliable simulator of a conveyor system which can be implemented to explore parameters interrelationships at the phase of system design. Computer runs were performed to analyze the interrelationships between operational parameters which characterize the explored conveyor system. The expert system was programmed in a way that provides a generic simulator, which can be employed in a large variety of conveyor systems.