模糊专家系统在铝电解控制中的应用

介绍以铝电解槽生产过程为对象,开发的铝电解模糊专家系统,阐述了其系统构成,主要功能及其工作原理和实际生产过程中的运行效果。     

化工过程实时状态监测与模糊诊断系统研究与实现

过程监测与故障诊断是化工过程工程中的一项重要任务，是保证生产过程安全运行、降低废品率的重要环节。本文在分析各种诊断方法的基础上，结合数据分析、专家系统、模糊逻辑以及面向对象分析等技术，提出并开发了一个化工过程实时监测与模糊诊断系统。该系统由数据校正、过程监测和模糊专家系统三部分组成，采用开放式结构，具有良好的易维护性和可扩充性。     

用模糊神经网络预测蘑菇生长过程

文章探讨了模糊神经网络的基本构造和原理,结合蘑菇生长过程预测系统重点分析了FNNC摸型的推理和学习方法。并在此基础上提出了TPH学习方法。该方法吸收了梯度下降算法和随机搜索算法的优点,能够使生长过程预测系统的学习以很大概率快速收敛在系统误差的最优点附近。最后文章指出模糊神经网络以及TPH学习算法在农业生产过程的应用。     

神经网络和模糊系统在故障诊断中的应用

本文提出了一种神经网络和模糊系统相结合的分级式故障诊断方法。神经网络通过对部分测量数据的处理，实现系统的回路级故障诊断，输出各回路故障出现的可信度。模糊系统通过对神经网络得到的初步诊断结果和其他测量值的处理，实现系统的元件级故障诊断，并对最终诊断结果作出解释。该方法融合了神经网络自适应学习能力强和模糊系统知识表达明确的优点，简化了神经网络学习数据获取及模糊推理规则建立的过程。通过对热硝酸冷却系统故障诊断的仿真，证明了该故障诊断方法的有效性。     

带有模糊逻辑系统的综合自动测控系统初步探讨

本文根据地空导弹武器测控系统发展的需要，提出了一种带有模糊逻辑系统的综合自动测控系统新方案。文章对该系统的组成、功能及其基本工作过程等作了扼要的介绍。     

基于修剪策略的D-FNN直接逆控制算法研究

神经网络是模拟人脑结构,它具有大规模并行及分布式信息处理能力,但是不能处理和描述模糊信息.模糊系统具有推理过程容易理解,但它很难实现自适应学习的功能.如果结合神经网络与模糊系统,可以取长补短.基于此,本文提出了一种新型动态模糊神经网络（Dynamic fuzzy neural network,D-FNN）学习算法.因为它具有结构和参数同时调整且学习速度快等优点,所以既可以在模糊逻辑系统中包含低级的神经网络学习和计算功能,也可以为神经网络提供高级的类似人的思维和推理的模糊逻辑系统.此外,本文还开发了生物医学工程应用算法程序,针对药物注射系统的直接逆控制案例进行了仿真,结果表明:D-FNN具有实时学习和控制能力强、参数估计和结构辨识同时进行等优点.     

DCS在循环注气生产过程中的应用

本文介绍了ＤＣＳ在首次于我国采用的循环注气生产过程中的应用，该系统功能合理，操作方便，安全可靠；文中还针对液化气分馏塔控制进行了模糊解耦的仿真实验研究     

基于模糊式识别的漏钢预报

提出了一种基于模糊模式识别和采用学习方法的模糊决策网络的漏钢预报方法，同时对热电偶测温系统做了改进。实验表明该模糊漏钢预报系统不但可以准确对温度模式进行分类和预测拉漏事故，而且对于连铸生产过程故障诊断和产品质量评价也有一定的指导意义。     

基于模糊模式识别的漏钢预报

提出了一种基于模糊模式识别和采用学习方法的模糊决策网络的漏钢预报方法，同时对热电偶测温系统做了改进．实验表明该模糊漏钢预报系统不但可以准确对温度模式进行分类和预测拉漏事故，而且对于连铸生产过程故障诊断和产品质量评价也有一定的指导意义     

模糊神经网络在火灾报警系统中的应用

提出一种利用神经网络和模糊推理系统设计火灾报警系统的方法，该系统将模糊系统和神经网络结合起来，实现模糊系统的自学习和自适应功能，提高火灾报警的准确性，减少了火灾报警系统漏报率和误报率。神经网络的学习方法提高了该系统智能化程度。实现了消防系统智能化。     

A fuzzy expert database system

Fuzzy concepts always exist in much of human reasoning as well as decision making. This paper presents a fuzzy expert database system which is an integration of a fuzzy expert system building tool called SYSTEM Z-II and a database management system called Rdb/VMS. This system is able to extract fuzzy data and terms stored in a database and used in the fuzzy reasoning in an expert system. It can also retrieve information by fuzzy database-queries which are generated by the expert system automatically. Many expert systems in different domain areas such as decision making can be constructed. Sample applications are described to demonstrate the flexibility and power of this system. The fuzzy query language defined and used in the system can also be used independently as a fuzzy enquiry tool in database applications.     

基于模糊推理的质量诊断专家系统的设计

以模糊推理为理论基础，根据专家系统的思想，通过对生产过程质量诊断基本要素的分析，建立了质量诊断专家系统算法的基本模型，对系统参数的确定方法进行了重点论述，并对实际应用中的一些问题提出了意见。     

基于数据库的电力设备故障诊断模糊专家系统的设计与实现

采用SQL Anywhere 5.0设计知识库。PowerBuilder6.5编程实现了电力设备故障诊断模糊专家系统,其知识的表示采用了模糊产生式表示式,引进了模糊匹配与加权模糊逻辑进行模糊推理,实现了一种较为理想的非精确推理。     

Analysis of assembly operations difficulty: a fuzzy expert system approach

Typical mechanical products can be assembled in various sequences of assembly operations. These sequences have high impact on the assembly time, machine utilization and even on the product quality. In order to select the best sequence of assembly operations, proper evaluation of the various sequences of assembly operations is required. This, in turn, requires the consistent evaluation of each assembly operation in the sequence. The assembly operations can be evaluated for various criteria, of which the operation difficulty is the most meaningful. This paper describes a methodology to analyse the assembly operations and calculates an operation's degree of difficulty using an expert system. This analysis consists of two steps: the first one identifies the main parameters that affect the assembly difficulty and assigns fuzzy triangular values to these parameters. The second step assigns weights to the parameters in order to maximize the agreement with a domain expert. The expert system analyses the difficulty of the assembly operation performed in two orientations: horizontal and vertical. The expert system then assigns a triangular fuzzy number as the aggregate measure of the operation's difficulty.     

模糊理论在专家系统中的应用研究

本文运用模糊理论结合产生式知识表示法,构造了一个模糊诊断专家系统的推理模型。     

基于模糊推理模型的专家系统的研究与应用

应用模糊推理理论的思想和方法设计和实现了一个燃煤锅炉事故诊断专家系统。本文详细介绍了系统的基本结构、知识表示和推理机制。系统采用模糊关系矩阵和基于框架的模糊推理相结合的推理方法,具有较高的准确性。最后给出了一个应用实例。     

模糊推理在空调系统故障诊断中的应用

针对空调系统的故障诊断问题及其特点，提出了一种基于诊断知识的模糊描述和模糊推理方法，阐述了空调系统故障诊断专家系统中前向推理、后向推理以及正反向混台推理模糊断言可信度的计算方法，并且给出了相应的实例。     

Modelling the software development process using an expert simulation system having fuzzy logic

This paper describes an intelligent computerized tool designed to aid managers of software development projects in planning, managing and controlling the development process of medium- to large-scale software projects. Systems dynamics is used to model and simulate the dynamic process of software development. The software development process is affected by some imprecise and vague variables that are treated as fuzzy variables. The simulation model is integrated with two expert systems. The fuzzy input variables to the system dynamics simulation model are handled by an input expert system having fuzzy logic. This expert system is designed to check the consistency of input variables. The simulation results are analysed by an output expert system having fuzzy logic. This expert system is designed to make recommendations based on experimentation with the simulation model.     

智能化农业信息处理系统中的模糊决策研究

文章在两个模糊决策理论的基础上，讨论了在农业专家系统中的综合模糊决策的应用。     

Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry

Reliable prediction of sales can improve the quality of business strategy. In this research, fuzzy logic and artificial neural network are integrated into the fuzzy back-propagation network (FBPN) for sales forecasting in Printed Circuit Board (PCB) industry. The fuzzy back propagation network is constructed to incorporate production-control expert judgments in enhancing the model's performance. Parameters chosen as inputs to the FBPN are no longer considered as of equal importance, but some sales managers and production control experts are requested to express their opinions about the importance of each input parameter in predicting the sales with linguistic terms, which can be converted into pre-specified fuzzy numbers. The proposed system is evaluated through the real world data provided by a printed circuit board company and experimental results indicate that the Fuzzy back-propagation approach outperforms other three different forecasting models in MAPE measures.