An expert system for selection of retaining walls and groundwater controls in deep excavation

A rule-based expert system has been built for selection of both retaining wall types and groundwater control methods in deep excavations in Wuhan city. For this expert system, a new type of generation rule is developed in which one condition is able to be defined with a “third state” that not only contributes directly to reaching the conclusion in a rule, but also factors into calculating the reliability of the conclusion. The traditional backward chaining technique has been improved to accommodate the change of a rule type and a fuzzy backward chaining method IRO has been established to increase reasoning flexibility. Using IRO as a fundamental element, it is convenient to form a complicated reasoning network in the inference engine. Finally, two knowledge bases are built from more than 100 case histories and other resources, and the new expert system proves to be effective in case studies.     

许昌市区域性暴雨集成预报系统

以新的预报流程和预报技术路线为指导，使用省台指导预报和数值预报产品等资料，通过专家系统、MOS、完全预报等预报方法，分别建立许昌市区域性暴雨预报诊断模型，在此基础上，使用VB6．0语言编程，建立许昌市区域性暴雨集成预报系统。     

开放的地图制图专家系统设计

本文把开放的思想引入地图制图专家系统中，详细论述了多知识表达的知识库、多向推理的推理机及开放的解释机制等关键问题。     

点状符号设计的推理模型

本文以地图符号的视觉变量和地图要素的表示等级为依据，详细介绍了地图设计专家系统中点状符号设计的推理模型。     

Experiences with an expert system for gold exploration in Botswana

This article describes initial experiences with an expert system in the scope of an exploration project in Botswana. A simple and easy-to-use expert system shell for personal computers was applied to construct an inference network for epigenetic gold deposits. The main objective, however, was not the automation of human intelligence but the structural analysis of domain knowledge for a target assessment. Aspects of human reasoning are discussed and compared with machine reasoning. Some actual problems concerning the inversion of rules under uncertainty, contrary evidences, and prior probabilities are discussed. Technical aspects like costs and schedule are included in the exploration model. Three different approaches for constructing an inference network are described.     

专家系统在 TM 图像分类中的应用

提高TM图像的分类精度,是图像处理及应用领域中一个很重要的研究课题。本文在总结已有成果基础上,首先利用现有的统计分类技术,对待分类图像进行预分类,并检测出“不确定”像元。然后综合光谱、地理、土壤类型、早期判别结果、目视判读经验等各种知识和信息,充分发挥专家系统的推理判断能力,对“不确定”像元的类别作进一步判别,使得整幅图像的分类精度得到改善。并据此初步建立了一个土地利用的分类系统。试验证明,这种分类方法的精度比仅用单一多光谱信息的统计分类法(最大似然法)提高约8％。     

EXPERT SYSTEM FOR THE CHARACTERIZATION OF LABORATORY SAMPLE INPUT SIGNALS:AUTOCORR

An expert system is presented for automated time series analysis of laboratory sample input signals.Thesystem,AUTOCORR,builds a model of the time series by identifying the processes that are present.These are an uncorrelated random process and,underlying this,possibly one or more of the following:a first-order autoregressive process,a trend and a periodic process.AUTOCORR has a knowledge baseof 44 rules and 41 facts for this purpose.The employed shell,INFER,allows the use of algorithmicprocedures.Elaborate tests with simulated signals show that AUTOCORR has a very low false positivescore and is successful in describing time series for laboratory simulation models.     

Knowledge-based systems as decision support tools in an ecosystem approach to fisheries: Comparing a fuzzy-logic and a rule-based approach

In an ecosystem approach to fisheries (EAF), management must draw on information of widely different types, and information addressing various scales. Knowledge-based systems assist in the decision-making process by summarising this information in a logical, transparent and reproducible way. Both rule-based Boolean and fuzzy-logic models have been used successfully as knowledge-based decision support tools. This study compares two such systems relevant to fisheries management in an EAF developed for the southern Benguela. The first is a rule-based system for the prediction of anchovy recruitment and the second is a fuzzy-logic tool to monitor implementation of an EAF in the sardine fishery. We construct a fuzzy-logic counterpart to the rule-based model, and a rule-based counterpart to the fuzzy-logic model, compare their results, and include feedback from potential users of these two decision support tools in our evaluation of the two approaches. With respect to the model objectives, no method clearly outperformed the other. The advantages of numerically processing continuous variables, and interpreting the final output, as in fuzzy-logic models, can be weighed up against the advantages of using a few, qualitative, easy-to-understand categories as in rule-based models. The natural language used in rule-based implementations is easily understood by, and communicated among, users of these systems. Users unfamiliar with fuzzy-set theory must “trust” the logic of the model. Graphical visualization of intermediate and end results is an important advantage of any system. Applying the two approaches in parallel improved our understanding of the model as well as of the underlying problems. Even for complex problems, small knowledge-based systems such as the ones explored here are worth developing and using. Their strengths lie in (i) synthesis of the problem in a logical and transparent framework, (ii) helping scientists to deliberate how to apply their science to transdisciplinary issues that are not purely scientific, and (iii) representing vehicles for delivering state-of-the-art science to those who need to use it. Possible applications of this approach for ecosystems of the Humboldt Current are discussed.     

专家证据权重法在矿产评价中的应用——以黑龙江省西北部金矿为例

由于黑龙江省西北部地区地质勘探程度低,而且研究区已知矿床（点）数目少,利用统计方法的证据权重法不能应用于该地区。为此,将黑龙江省西北部地区的基础地质、区域成矿规律、金矿床成矿特征等方面取得的认识建立了一个“专家知识库”,并与“证据权重法”结合起来,建立一个基于专家证据权重法的矿产资源定量评价系统。利用该系统对黑龙江省西北部金矿进行预测并取得了很好的效果,为在黑龙江省西北部进一步找矿奠定了基础。