基于邻域统计特性的概率神经网络及其在自动目标识别中的应用

在概率神经的一种改进模型－ＦＤＯ网络的基础上，提出在设计网络收敛域时进一步考虑每一像素点周围８邻域的影响，对网络的作用函数加以修，使改进后的网络具有稳定性好且收敛速度快的优点。通过实验对改进前后网络的识别性能加以比较，证明改进后的网络特别适用于噪声图像的识别。     

Knowledge-based diagnosis of drill conditions

One major bottleneck in the automation of the drilling process by robots in the aerospace industry is drill condition monitoring. This paper describes a system approach to solve this problem through the advancement of new machine design, sensor instrumentation, metal-cutting research, and intelligent software development. All drill failures can be detected and distinguished: chisel edge wear, flank wear, crater wear, margin wear, corner wear, breakage, asymmetry, lip height difference, and chipping at lips. However, in the real manufacturing environment, different workpiece materials, drill size, drill geometry, drill material, cutting speed, feed rate, etc. will change the criteria for judging the drill condition. The knowledge base used for diagnosing the drill failures requires a huge data bank and prior exhaustive testing. A self-learning scheme is therefore introduced to the machine in order to acquire the threshold history needed for automatic diagnosis by using the same new tool under the same drilling conditions.     

人工智能方法用于熔喷过程在线检测的研究

熔喷生产最终产品质量的控制，对于过程优化具有重要的意义。产品质量的在线检测是过程监测与质量控制必不可少的。本文首次在熔喷系统中引入人工智能的研究方法，对熔喷非织造布的厚度与纤维直径进行在线预测。实测数据与人工神经网络的预测结果吻合较好，从而证实了人工神经网络用于模拟熔喷过程的可行性。网络的输入包括：挤出机温度、喷头温度、熔融体挤出速率、空气流率及接收距离。神经元计算的输出是纤维直径与熔喷非织布的厚度。文中进一步提出了将神经网络与专家系统相结合的研究路线，以实现熔喷过程的优化控制。     

汽油辛烷值智能调合系统

采取一种能够在线学习、不断提高、建立一系列模型的策略，提出了一种具有学习功能的汽油辛烷值智能调合系统。该系统可以根据成品汽油辛烷值指标、生产成本和市场价格等因素提供一个较好的油品调合调度方案。实际应用结果表明，利用参数学习的方法计算调合汽油辛烷值是可行的。     

应用人工神经网络优化五点法水平井井网

水平井直井联合布井方式越来越多地应用到油田的实际开发中，但是井网的选择与优化方面的研究比较少，特别是没有根据不同开发阶段变化的生产动态对水平井井网进行优化。应用人工神经网络技术，在进行数值模拟计算的基础上，制作样本并训练网络，可预测任意面积、任意水平井长度下的五点法水平井井网在不同开发阶段的生产动态，优化出不同生产时间和不同井网面积条件下最优井网穿透比，即生产10a时最优井网穿透比为0．55～0．8。与数值模拟结果进行对比，最大误差在1％以内，表明这种方法既快速简便又具有较高的精确性，可以有效地指导五点法水平井井网优化设计。     

Expert Systems for Construction Project Monitoring

Potential applications of knowledge based expert systems in the area of construction project monitoring and control are described. Originally developed from research in artificial intelligence, these systems are computer programs that can undertake intelligent tasks currently performed by highly skilled people. While some project monitoring can be accomplished by algorithmic procedures, the capability of knowledge based expert systems to deal with illstructured problems and to be extensively modified over time make them desirable for application in this area. Sample applications and heuristic rules in scheduling and inventory control are provided.     

Semantic Web Mining: State of the art and future directions

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. This survey analyzes the convergence of trends from both areas: More and more researchers are working on improving the results of Web Mining by exploiting semantic structures in the Web, and they make use of Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself.The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today’s Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable.     

商务智能在ERP系统中的应用

ERP系统属于典型的联机事务处理系统,不可避免的存在许多不足,无法提供企业决策所需的决策信息。商务智能是一种正在快速发展的技术,它在ERP中的应用有效的解决ERP存在的问题。     

MV2000T智能变送器

较全面地介绍了ABB公司MV2 0 0 0T智能变送器的市场开发背景、工作原理、技术规格、性能特点及设计选型要点     

Cleanbot-Ⅰ擦窗机器人的智能化技术

本文简述了擦窗机器人智能化的主要概念．介绍了Ｃｌｅａｎｂｏｔ－Ｉ擦窗机器人系统的结构特点、主要组成部分、工作原理，操作方式，未知局部环境的模型建立，各类内、外传感器的结构、原理和信息融合技术，以及路径规划的方法．