An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential

Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM. A model was considered successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the other outcomes, which ranged from 79% to 86%. We found that the highest balanced accuracy of any of the expert systems evaluated was 65% when making global predictions. For substances within the domain of TIMES-SS, however, balanced accuracies for the two datasets were found to be 79% and 82%. In those cases where a chemical was within the TIMES-SS domain, the TIMES-SS skin sensitisation hazard prediction had the same confidence as the result from LLNA or GPMT.     

化学学科视域下课堂互动双编码模型的应用研究

以弗兰德斯互动分析系统为理论基础,构建了具有化学学科特征的课堂互动双编码分析模型。以获得安徽省高中化学优质课大赛一等奖的1名优秀新手型教师和1名专家型教师的课堂为例,从课堂互动矩阵、动态折线图、课堂互动变项、教师表征转换水平等4个方面的比较与分析入手,全面介绍了该双编码模型在课堂分析中的应用。     

基于案例推理方法在惯性导航故障诊断专家系统的应用

以测量船惯性导航系统为例,为解决其故障诊断专家系统知识瓶颈问题,特别是突发、原因不详的故障,利用专家知识和以往的工作经验积累,在故障诊断专家系统中融入了基于案例的推理方法。这种推理方法把知识获取简化为领域内经验知识的收集,并以此为基础构造案例库;把基于规则的推理转化为基于案例推理,即在案例库中检索相似的经验知识。采用基于案例推理的方法,可以简化知识获取的过程,求解效率高、质量高,具有持续的学习能力,能有效提高故障诊断系统的智能化程度。文中重点介绍了构建该故障诊断专家系统的案例知识表示方法、案例的索引和检索算法等关键技术。     

诊断和修理航空继电器故障的优化系统

为了减少目前航空继电器用于发现和修理故障的费用 ,本文建立了基于规则、事实以及其自身经验的一个专家系统——适应性诊断系统 ADS( A daptive Diagnostic System) .该系统利用推理对航空继电器检测和替换顺序进行了优化 ,使节省的费用大约为 50 % .     

群组决策特征根法

本文提出了一个群组决策的特征根法GEM（Groupeigenvaluemethod），它彻底克服了判断矩阵的不一致性，为决策支持系统中的专家选择开辟了新路．     

汽车发动机智能故障诊断专家系统的开发

采用VB语言,根据诊断树理论,构造了一个基于神经网络的汽车发动机智能故障诊断专家系统．对故障树理论、神经网络的建立和系统的结构功能等进行了探讨．给出了工程应用的实例。     

关于模糊逻辑的—场争论

本文介绍最近发生的关于模糊逻辑的意义和应用的一场争论。并提出笔者的见解。     

A systematic approach for the generation and verification of structural hypotheses

During the process of molecular structure elucidation the selection of the most probable structural hypothesis may be based on chemical shift prediction. The prediction is carried out using either empirical or quantum‐mechanical (QM) methods. When QM methods are used, NMR prediction commonly utilizes the GIAO option of the DFT approximation. In this approach the structural hypotheses are expected to be investigated by scientist. In this article we hope to show that the most rational manner by which to create structural hypotheses is actually by the application of an expert system capable of deducing all potential structures consistent with the experimental spectral data and specifically using 2D NMR data. When an expert system is used the best structure(s) can be distinguished using chemical shift prediction, which is best performed either by an incremental or neural net algorithm. The time‐consuming QM calculations can then be applied, if necessary, to one or more of the ‘best’ structures to confirm the suggested solution. Copyright © 2009 John Wiley & Sons, Ltd.     

一种用于诊断电子设备故障的专家系统

本文着重从分析电子设备故障诊断的人类专家的实际工作特点入手,指出单纯采用产生式规则的专家系统的不足之处,进而提出一个同时使用框架及产生式规则的专家系统—电子设备故障诊断专家系统;同时描述了该系统的部分算法及实现原理.通过分析该系统的建立过程,本文旨在强调这样一个观点:选择适合于领域特点的知识表示方法及适当的推理算法对于建立一个实用的专家系统是很重要的.     

A Kind of Approximate Reasoning Principles

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