制造型企业财务诊断的设计与实现

企业的自我诊断与评价方法的研究，对实现我国的现代企业化管理有十分重要的意义。该文介绍了制造类企业的自我诊断与评价方法系统的功能结构开发环境，讨论了财务诊断子系统的功能设计，数据库设计和接口设计的实现，并重点分析了财务诊断思想与实现方法。     

制造型企业财务诊断系统的设计与实现

企业的自我诊断与评价方法的研究,对实现我国的现代化企业管理有十分重要的意义。该文介绍了制造类企业的自我诊断与评价方法系统的功能结构与开发环境,讨论了财务诊断子系统的功能设计,数据库没计和接口设计的实现,并重点分析了财务诊断的功能设计思想与实现方法。     

中小企业诊断本体的构建方法

对本体论应用到企业诊断领域进行了探讨.基于知识密集型企业诊断过程,提出了一种用IDEF5本体论荻取方法以及OWL来分析,提取、模型化企业诊断本体的方法.对企业诊断知识和利用IDEF建模方法建立企业诊断模型进行了概要的介绍,介绍了领域本体的构建.最后以企业诊断系统为例介绍了本体构建,并用OWL语言进行了描述.     

基于集成化企业模型体系的企业建模与优化

本文探讨企业建模与优化方法。首先分析集成化企业模型体系的特点与构成,说明其对企业的自身认识和问题诊断的支持。继而借鉴面向对象思想研究建立企业模型体系的过程方法,最后从对象优化、结构优化和过程优化几方面探讨基于集成化企业模型体系的企业优化方法。     

CIMS总体设计分析

ＣＩＭＳ总体设计是一种阶段化的方法，本文对ＣＩＭＳ总体设计进程进行了分析。首先讨论了总体设计的生命周期，分析了各阶段的原则，目标，方法和内容，特别提出了企业诊断概念，指出处理好企业诊断与ＣＩＭＳ总体设计的关系对ＣＩＭＳ的哲理的扎根应用和国有企业竞争力的重要意义，最后展望了基于ＣＡＳＥ平台的总体设计趋势。     

CIMS总体设计分析

CIMS总体设计是一种阶段化的方法，本文对CIMS总体设计进程进行了分析。首先讨论了总体设计的生命周期，分析了各阶段的原则、目标、方法和内容，特别提出了企业诊断的概念，指出处理好企业诊断与CIMS总体设计的关系对CIMS哲理的扎根应用和国有企业竞争力的提高的重要意义，最后展望了基于CASE平台的总体设计趋势。     

企业评价与诊断原型系统的设计

企业诊断是科学评判企业经营成果、指导企业管理的有效手段。文章提出了一个基于知识库和数据仓库的企业评价与诊断系统的原型,并描述了该原型系统的组成结构及其具体实现机制,讨论了系统实现中的关键技术问题和解决方案,其中包括多值逻辑的不精确推理、导航知识库的组织等。     

企业模型诊断的知识表达与知识库构建

针对制造类企业模型的特点，通过吸收标记语言的优点，给出了企业模型诊断的知识表达方法；并在此基础上构建了用于智能诊断系统的知识库。并通过一个应用实例验证了模型诊断知识表达方法的有效性以及智能诊断系统的实用性。     

基于模糊覆盖集的企业诊断模型及其求解策略

针对企业诊断领域缺乏合理模型和科学方法论指导的现状，提出一个形式化的基于模糊覆盖集的企业诊断模型，并将此模型与企业AS-IS(当前系统)建模过程进行关联，给出了从企业AS-IS模型到诊断模型的映射方法，得到一种易于操作的实例化的企业诊断模型，进而针对该诊断模型给出了相应的求解策略。     

基于信息技术服装企业管理系统的研究

本文讨论了服装企业管理的现状与发展，介绍了信息技术的发展对服装企业管理的影响，最后对基于信息技术的服装企业管理信息系统进行了分析和研究。     

投资项目管理的知识支持系统

从系统工程角度分析投资项目管理，针对建设投资项目系统存在的不确定性，提出建立了一个对整个投资项目管理周期的市场环境和企业的生产经营信息进行存储管理的知识库，用来辅助企业做出各种决策。采用面向对象技术构造知识库开发模型，给出了相应的模型结构，建立了现实性校验流程图，知识支持系统自始至终优化管理建设投资项目，增强了决策信息的可靠性，使项目投资最优化。     

A fuzzy reasoning based diagnosis system for X control charts

This paper describes a new diagnosis system, which is based on fuzzy reasoning to monitor the performance of a discrete manufacturing process and to justify the possible causes. The diagnosis system consists chiefly of a knowledge bank and a reasoning mechanism. The knowledge bank provides knowledge of the membership functions of unnatural symptoms that are described by Nelson's rules on X control charts and knowledge of cause-symptom relations. We develop an approach called maximal similarity method (MSM) for knowledge acquisition to construct the fuzzy cause-symptom relation matrix. Through the knowledge bank, the diagnosis system can first determine the degrees of an observation fitting each unnatural symptom. Then, using the fuzzy cause-symptom relation matrix, we can diagnose the causes of process instability. In conclusion we provide a numerical example to illustrate the system.     

Management of system development knowledge: a cognitive approach

The management of system development knowledge (SDK) is currently sub-optimal regarding the system developer's learning and use of the knowledge due to its inherently complex and cumbersome nature. In this work, we have identified and categorised different approaches to the management of SDK generally having instrumental and technical subject matter. To complement the current literature in this field of study, our approach to the management of SDK has taken into account the system developer's cognitive processing concerns. As such, we have proposed and successfully tested a strategic method for SDK management in a real working situation. In this empirical study, the implementation of an artificial knowledge structure has been shown to be useful as a means of decreasing the system developer's cognitive processing load as regards SDK. The first of two implications is such that cognitive consideration in relation to SDK management has further developmental potential. The second implication is that the system development environment can provide cognitive support to the system developer.     

中小规模研究性企业知识管理体系建设探索

研究型企业深刻意识到知识管理体系对企业的重要性．建立知识管理体系过程中出现的各类问题导致知识管理体系推动研究型企业进步的效率较低．笔者所在单位在长期管理信息系统建设过程中,从知识收集、整理归纳、知识共享、知识创新等环节进行方法研究和实践探索,取得了一定效果,企业内部知识体系逐步进入有序建设,有效推动了企业知识创新．     

ITONUS: Expert system for machining on a lathe

A microcomputer-based expert system for the diagnosis of lathe machining operations has been developed using the EXSYS shell on an IBM AT. Interviews with a journeyman machinist resulted in an initial knowledge base of rules containing basic concepts and relationships concerning set-up and control of lathe machining. The system provides the user with analysis and advice regarding the diagnosis and certain set-up aspects of common lathe operations, and has shown that it is feasible to elicit and mimic at least a portion of an expert machinist's knowledge and special skills.     

化工过程实时故障诊断专家系统的研究与开发

讨论了复杂化工过程实时故障诊断专家系统的设计与实现。对于该系统的系统结构、知识库结构以及推理机的设计进行了详细介绍。尤其是讨论了一种新的知识规则冲突消解策略——前提排序策略以及内存知识库中知识规则选择策略。并以润滑油生产过程为例,讨论了系统的故障诊断过程。实际应用表明,该系统能够及时、迅速地对故障做出响应,满足了生产需求。     

基于知识蒸馏的钢铁高炉煤气系统建模方法

钢铁企业高炉煤气系统具有波动性大、时变性强、不确定性高等特点,对其未来产消趋势进行准确的建模预测有助于企业的高效决策与节能减排.文章提出了一种基于知识蒸馏的高炉煤气系统建模方法,为了提高训练过程中的拟合精度,在教师网络中建立了基于长短期记忆网络的序列到序列模型来提取样本的中间特征.进而,提出了融入教师模型中间特征的知识蒸馏策略,建立了考虑中间特征蒸馏损失与预测均方误差的损失函数,对知识蒸馏过程及预测偏差进行评估.通过国内大型钢铁企业高炉煤气系统实际运行数据的实验验证,表明了本文所提建模方法的有效性,可为后续的能源系统优化调度提供支撑.     

故障诊断专家系统中知识库组织和维护技术的研究

在开发化工过程实时故障诊断专家系统的基础上,本文讨论了知识库的组织和维护技术,对知识表示和知识库结构进行了详细介绍。在知识库维护方面,采用面向对象的方法描述领域知识,并实现知识获取和转换;对于知识校验,提出一种基于有向图的知识校验方法。以润滑油生产过程为例,讨论了系统的知识校验过程。本文讨论的技术和策略已应用于润滑油过程实时故障诊断专家系统。实际应用表明,该技术和策略保证了知识库和专家系统的稳定和高效率。     

An expert system for real-time fault diagnosis of complex chemical processes

This paper presents the development and implementation of an expert system for real-time fault diagnosis of chemical processes. The expert system is applied as a real-time computer aided decision support system, providing operation suggestions to help field operators when abnormal situations occur. The knowledge base structure, representation of knowledge, and access to expertise are technically considered. Industrial applications to the fluid catalystic cracking process in refinery indicate that the expert system diagnoses abnormal events efficiently and promptly.     

A framework for interval-valued information system

Interval-valued information system is used to transform the conventional dataset into the interval-valued form. To conduct the interval-valued data mining, we conduct two investigations: (1) construct the interval-valued information system, and (2) conduct the interval-valued knowledge discovery. In constructing the interval-valued information system, we first make the paired attributes in the database discovered, and then, make them stored in the neighbour locations in a common database and regard them as ‘one’ new field. In conducting the interval-valued knowledge discovery, we utilise some related priori knowledge and regard the priori knowledge as the control objectives; and design an approximate closed-loop control mining system. On the implemented experimental platform (prototype), we conduct the corresponding experiments and compare the proposed algorithms with several typical algorithms, such as the Apriori algorithm, the FP-growth algorithm and the CLOSE+ algorithm. The experimental results show that the interval-valued information system method is more effective than the conventional algorithms in discovering interval-valued patterns.