降低成品油二次物流运输成本的思考

介绍了传统成品油进货和管理模式存在的诸如成品油物流以行政区划、中问环节多、信息化程度不高、运输路线未优化造成物流成本提高等问题。提出要降低成品油二次物流运输成本，当务之急是加强成品油物流的信息化建设；调整管理模式，打破行政区域界限，开展经济辐射半径内的库站物流配送；引进竞争机制，打破运输垄断，一、二次物流结合，大、小车型搭配，提高运营效率；做好运杂费全面预算、核算及运行费用的过程控制。     

人工智能的原理及应用

介绍了人工智能的发展，并对改进的神经网络专家系统的优越性做了介绍，指出了神经网络专家系统广阔的应用前景及实现。     

对印制电路板环境冲击评估的研究

随着印制电路板产业飞速发展,其引发的环境问题日益受到广泛的关注。然而长期以来如何有效地进行环境冲击评估是业内研究的重点和难点。而本文采用了一种智能的简化分析方法来进行全面的环境冲击评估,以提高评估的经济效益和准确度,并希望能为决策者提供一个可供参考的环境冲击评估的理念和方法。     

制造业企业竞争情报系统建设浅析

讨论了制造业企业信息化进程中包含竞争情报系统的必要性。论述了该类企业竞争情报系统的内涵及功能特征。较详细地介绍了相应系统常用外部数据资源内容及各自应用特点;此外本文还简要地说明了该类系统现有开发支持工具软件、开发关键步骤等内容。     

Integration framework for intelligent manufacturing processes

In this article, we describe a new approach to applying distributed artificial intelligence techniques to manufacturing processes. The construction of intelligent systems is one of the most important techniques among artificial intelligence research. Our goal is to develop an integrated intelligent system for real time manufacturing processes. An integrated intelligent system is a large knowledge integration environment that consists of several symbolic reasoning systems (expert systems) and numerical computation packages. These software programs are controlled by a meta-system which manages the selection, operation and communication of these programs. A meta-system can be implemented in different language environments and applied to many disciplines. This new architecture can serve as a universal configuration to develop high performance intelligent systems for many complicated industrial applications in real world domains.To whom all correspondence should be addressed.     

基于事例学习的建筑结构的虚拟实现

提出基于事例学习的目标规划问题,并进一步研究了建模思想的可行性和建模方法的可操作性。利用知识工程、机器学习理论,人工智能技术来存贮和运用专家的经验,实现了在虚拟环境中建筑结构设计、施工,设备的仿真试验,并可对初学者或尚无经验的设计、施工者进行培训学习。该项研究为目标规划问题开辟了基于事例学习的模型生成途径。     

DCOP FOR SMART HOMES: A CASE STUDY

The aim of this article is to bring forth the issue of integrating the services provided by intelligent artifacts in Ambient Intelligence applications. Specifically, we propose a Distributed Constraint Optimization procedure for achieving a functional integration of intelligent artifacts in a smart home. To this end, we employ Adopt-N , a state-of-the-art algorithm for solving Distributed Constraint Optimization Problems (DCOP). This article attempts to state the smart home coordination problem in general terms, and provides the details of a DCOP-based approach by describing a case study taken from the RoboCare project. More specifically, we show how (1) DCOP is a convenient metaphor for casting smart home coordination problems, and (2) the specific features which distinguish Adopt-N from other algorithms for DCOP represent a strong asset in the smart home domain.     

A prolog based expert system for the allocation of quality assurance program resources

The worldwide proliferation of fraudulent materials has brought about the need for a new approach to the control of purchased material quality. Nuclear power, defense, aerospace and many other industries are affected by the supply of poor quality clones that presume to be original replacement parts. Safety considerations abound as these highly defective materials are used in systems that are critical to the preservation of human lives. Commonly utilized quality assurance programs have not effectively stopped the influx of fraudulent materials. These programs fail to concentrate inspection efforts on materials and inspection attributes that would effectively prevent the acceptance of fraudulent materials. herein a solution is presented to this problem in the form of an expert system application. Information commonly available in industry is formulated into a knowledge based system wherein advisories are given to the user regarding key purchased material receipt inspection strategies.     

Application of Support Vector Machines in Assessing Conceptual Cost Estimates

Total conceptual cost estimates and the assessment of the quality of these estimates are critical in the early stages of a building construction project. In this study, the support vector machine (SVM) model for assessing the quality of conceptual cost estimates is proposed, and the application of SVM in construction areas is investigated. The results show that the SVM model assessed the quality of conceptual cost estimates slightly more accurately than the discriminant analysis model. This shows that using the SVM has potential in construction areas. In addition, the SVM model can assist clients in their evaluation of the quality of the estimated cost and the probability of exceeding the target cost, and in their decision on whether or not it is necessary to seek a more accurate estimate in the early stages of a project.     

智能工程与控制技术：历史,发展与未来

本文综述了智能工程和控制技术的发展历程和基本问题。文中着重论述了人工智能在过程控制系统中的必要性及开发实时智能控制系统的步骤；对符号推理系统、耦合推理系统、人工神经网络和集成分布式智能系统的特点和局限进行了比较。最后讨论了计算机集成过程系统（ＣＩＰＳ）的基本问题、基础技术和发展前景。