光学透镜自动设计智能化的计算方法

为改善镜头自动设计的计算方法,充分考虑人工光学设计经验,并借助构造多种价值函数以及线性最小二乘法和离散变量的单纯型方法,利用一个智能专家系统控制求解不等式组.在求解中,对玻璃变量和厚度等做变量替换以消除不等式约束,并且引入协调因子平衡变量的改变量.     

Fuzzy数学在涡喷发动机滑油故障诊断中的应用

将模糊数学方法引入到涡喷发动机滑油故障诊断中 ,提出了由历史数据及专家优序数综合确定模糊隶属度的方法 ,建立了模糊诊断模型 ,解决了针对一种或数种故障征兆 ,如何准确 ,快速地找到引起故障的真正原因 ,从而为飞机的故障诊断维修工作提供了一种科学、可行的新方法 .     

Bootstrap classification and point-based feature selection from age-staged mouse cerebellum tissues of matrix assisted laser desorption/ionization mass spectra using a fuzzy rule-building expert system

A bootstrap method for point-based detection of candidate biomarker peaks has been developed from pattern classifiers. Point-based detection methods are advantageous in comparison to peak-based methods. Peak determination and selection are problematic when spectral peaks are not baseline resolved or on a varying baseline. The benefit of point-based detection is that peaks can be globally determined from the characteristic features of the entire data set (i.e., subsets of candidate points) as opposed to the traditional method of selecting peaks from individual spectra and then combining the peak list into a data set. The point-based method is demonstrated to be more effective and efficient using a synthetic data set when compared to using Mahalanobis distance for feature selection. In addition, probabilities that characterize the uniqueness of the peaks are determined.This method was applied for detecting peaks that characterize age-specific patterns of protein expression of developing and adult mouse cerebella from matrix assisted laser desorption/ionization (MALDI) mass spectrometry (MS) data. The mice comprised three age groups: 42 adults, 19 14-day-old pups, and 16 7-day-old pups. Three sequential spectra were obtained from each tissue section to yield 126, 57 and 48 spectra for adult, 14-day-old pup, and 7-day-old pup spectra, respectively. Each spectrum comprised 71,879 mass measurements in a range of 3.5-50 kDa. A previous study revealed that 846 unique peaks were detected that were consistent for 50% of the mice in each age group (C. Laurent, D.F. Levinson, S.A. Schwartz, P.B. Harrington, S.P. Markey, R.M. Caprioli, P. Levitt, Direct profiling of the cerebellum by MALDI MS: a methodological study in postnatal and adult mouse, J. Neurosci. Res. 81 (2005) 613-621.).A fuzzy rule-building expert system (FuRES) was applied to investigate the correlation of age with features in the MS data. FuRES detected two outlier pup-14 spectra. Prediction was evaluated using 100 bootstrap samples of 2 Latin-partitions (i.e., 50:50 split between training and prediction set) of the mice. The spectra without the outliers yielded classification rates of 99.1 ± 0.1%, 90.1 ± 0.8%, and 97.0 ± 0.6% for adults, 14-day-old pups, and 7-day-old pups, respectively. At a 95% level of significance, 100 bootstrap samples disclosed 35 adult and 21 pup distinguishing peaks for separating adults from pups; and 8 14-day-old and 15 7-day-old predictive peaks for separating 14-day-old pup from 7-day-old pup spectra. A compressed matrix comprising 40,393 points that were outside the 95% confidence intervals of one of the two FuRES discriminants was evaluated and the classification improved significantly for all classes. When peaks that satisfied a quality criterion were integrated, the 55 integrated peak areas furnished significantly improved classification for all classes: the selected peak areas furnished classification rates of 100%, 97.3 ± 0.6%, and 97.4 ± 0.3% for adult, 14-day-old pups, and 7-day-old pups using 100 bootstrap Latin partitions evaluations with the predictions averaged. When the bootstrap size was increased to 1000 samples, the results were not significantly affected. The FuRES predictions were consistent with those obtained by discriminant partial least squares (DPLS) classifications.     

基于神经网络的多种油样分析技术融合诊断

针对4种最常用的油样分析技术(铁谱、光谱、颗粒计数及理化指标分析)的信息融合问题，依据基于规则的专家系统方法，建立了各油样分析技术的子专家诊断系统；依据专家经验建立各子专家系统的诊断结果与故障论域中各故障模式的关系，得到了用于神经网络学习的训练样本．在此基础上，通过对神经网络进行训练，并将待分析油样的各子专家系统诊断结论输入训练成功的网络，即得到融合诊断结果．实例分析表明所建立的分析方法便捷有效．     

A rule-based expert system for chemical prioritization using effects-based chemical categories

A rule-based expert system (ES) was developed to predict chemical binding to the estrogen receptor (ER) patterned on the research approaches championed by Gilman Veith to whom this article and journal issue are dedicated. The ERES was built to be mechanistically transparent and meet the needs of a specific application, i.e. predict for all chemicals within two well-defined inventories (industrial chemicals used as pesticide inerts and antimicrobial pesticides). These chemicals all lack structural features associated with high affinity binders and thus any binding should be low affinity. Similar to the high-quality fathead minnow database upon which Veith QSARs were built, the ERES was derived from what has been termed gold standard data, systematically collected in assays optimized to detect even low affinity binding and maximizing confidence in the negatives determinations. The resultant logic-based decision tree ERES, determined to be a robust model, contains seven major nodes with multiple effects-based chemicals categories within each. Predicted results are presented in the context of empirical data within local chemical structural groups facilitating informed decision-making. Even using optimized detection assays, the ERES applied to two inventories of >600 chemicals resulted in only ~5% of the chemicals predicted to bind ER.     

拉索桥梁安全性与耐久性评估的专家系统设计

应用模糊神经网络开发了以斜拉桥为背景的拉索桥梁安全性与耐久性评估专家系统。该系统能够同时处理数值型和语言描述型变量。根据桥梁监测过程中所获得的数据，它能对桥梁总体及其各个部分的状况进行评估，及时获得桥梁运行状态信息，评估其退化及损伤程度，对大型桥梁的现代化管理具有重要的现实意义。阐述了评估系统的工作原理及其实现方法，在介绍系统结构及各模块功能的同时，以斜拉桥试验为例展示该系统用于桥梁安全性及耐久性评估的部分功能。     

基于CLIPS的机载光电跟踪设备故障诊断专家系统研究

针对机载光电跟踪设备传感器种类多、单元部件结构复杂和急需快速故障定位的要求,设计了机载光电跟踪设备故障诊断专家系统。通过建立跟踪系统故障树并分析其故障特点,确定了模糊多值产生式规则的知识表示方式和冲突消解策略,构建了专家系统知识库和推理机;同时结合数据库建立的故障表和规则表,实现专家系统解释器功能;最后将CLIPS嵌入VC设计友好人机交互界面。实验表明,该专家系统操作方便,能快速准确定位故障、解释故障成因以及提供维修建议。     

药物气相色谱分析专家系统的柱系统推荐

报道了药物气相色谱分析柱系统推荐专家系统 .该系统可提供文献报道的 GC分析方法及文献出处 ;判断样品能否直接采用 GC分析 ,推荐固定相、柱温、固定液用量范围、检测器、载气等 ,并能对所推荐的色谱初始条件进行优化 .对固定相 ,系统可分别从 3个通道给予推荐 ,且选择通道的优先顺序依次为特殊组分 (同系物 ,异构体 )、组分的 Kováts指数以及组分的结构和极性 .本文以 Turbo Prolog为程序设计语言 ,采用产生式规则和谓词逻辑的知识表达方式以及深度优先搜索的正向链推理控制策略 ,在 IBM PC机上编程实现了这一系统 .     

基于IGA-BP神经网络和专家系统的我国银行流动性风险预警研究

以因子分析主成分方法选取预警指标;以免疫遗传算法对BP神经网络收敛速度较慢、易陷入局部极小等缺陷进行改进,形成IGA-BP神经网络.采用IGA-BP神经网络对银行的流动性风险进行预警,并提出以拥有强大知识库的专家系统对其输出的预警信号进行进一步核准和验证,确保预警信号的有效性,构建我国商业银行流动性风险预警机制.     

Computer-aided fault diagnosis in technical systems: An expert system for fault identification in the vacuum system of a mass spectrometer

We took a critical look on currently common methods for constructing expert systems and examined closely their applicability for computer-aided fault diagnosis. We deemed these methods not appropriate for this domain and presented our Knowledge Processing Facility KNOPF as an alternative. By means of KNOPF/MS, an expert system for computer-aided fault diagnosis in the vacuum system of a mass spectrometer implemented by using KNOPF, we demonstrated the applicability of our approach.