使用遗传算法的迷宫学习

本文试用遗传计算及决策制定方法来实现机器人有认识迷宫意向的能力，这里“意向”是指遵循对迷宫特有的路径规则所出的决定，令机器人在两个相对的迷宫中行走学习，一个迷宫路径是基于同样的意向，另一个则基于不同的意向，研究结果确认了已达成的意向学习。     

大规模数据库中的知识获取

一、前言数据是知识的潭泉,拥有大量的数据与拥有许多有用的知识完全是两回事.为了有效地利用大量的公共数据,必须更好地理解这些数据,并从其中快速、准确地发现知识.这里所说的知识是指大量数据中存在的规律性(r egularity)或不同属性值之间所存在的[I F THEN〕规则.将所获取的知识附加于仅由事实数据(fact data)构成的传统数据库上,既可强化数据库的查询能力,又可给数据库提供推理能力,     

国外MCM及其主要制造技术的发展现状

MCM具有胜过PCB、LSI和一般HIC的诸多优点,正在逢勃发展,可望成为九十年代的代表性技术。本文从市场和技术两个方面评述MCM的发展潜力,重点介绍近年来国外MCM主要制造技术的现状及发展态势,试图引起人们对它的关注。     

Design and Implementation of a Flexible Manufacturing Control System Using Neural Network

Design and implementation of a sequential controller based on the concept of artificial neural networks for a flexible manufacturing system are presented. The recurrent neural network (RNN) type is used for such a purpose. Contrary to the programmable controller, an RNN-based sequential controller is based on a definite mathematical model rather than depending on experience and trial and error techniques. The proposed controller is also more flexible because it is not limited by the restrictions of the finite state automata theory. Adequate guidelines of how to construct an RNN-based sequential controller are presented. These guidelines are applied to different case studies. The proposed controller is tested by simulations and real-time experiments. These tests prove the successfulness of the proposed controller performances. Theoretical as well as experimental results are presented and discussed indicating that the proposed design procedure using Elman's RNN can be effective in designing a sequential controller for event-based type manufacturing systems. In addition, the simulation results assure the effectiveness of the proposed controller to outperform the effect of noisy inputs.     

深基坑支护结构计算的有限元方法

针对软土地基的特性，本文提出了考虑土体抗力释放与结构模型随施工过程改变的新杆系有限元法，并 编制了求解支护结构内力与变形的计算程序，通过对事例分析．计算结果与实际情况非常吻合，证明了该方法的合理 性。     

深穿透复合射孔技术在中原油田的应用

深穿透复合射孔是一项把射孔与高能气体压裂两种技术有机地结合在一起的综合改造油气层的新技术。重点对它的技术原理，包括设计原理、枪身内火药燃烧气体对射孔孔眼的冲刷作用原理、火药燃烧气体射流的高能气体压裂作用原理等进行了研究与探讨，同时对它的施工工艺、现场应用等方面进行了阐述，经中原油田189口井现场应用证明，其工艺简便，成本低廉，可实现多层跨隔层使用，处理后增产效果显著，投入产出比高，可代替传统的聚能射孔技术，具有广阔的推广和应用价值。     

FILIP: A fuzzy intelligent information system with learning capabilities

FILIP (fuzzy intelligent learning information processing) system is designed with the goal to model human information processing. The issues addressed are uncertain knowledge representation and approximate reasoning based on fuzzy set theory, and knowledge acquisition by “being told” or by “learning from examples”. Concepts that can be “learned” by the system can be imprecise (fuzzy), or the knowledge can be incomplete. In the latter case, FILIP uses the concept of similarity to extrapolate the knowledge to cases that were not covered by examples provided by the user. Concepts are stored in the Knowledge Base and employed in intelligent query processing, based on flexible inference that supports approximate matches between the data in the database and the query.

The architecture of FILIP is discussed, the learning algorithm is described, and examples of the system's performance in the knowledge acquisition and querying modes, together with its explanatory capabilities are shown.     

深层搅拌水泥桩复合地基在工程中的应用

简要介绍了深层搅拌水泥桩的加固机理和适用条件。详细阐述了深层搅拌水泥桩的加固设计，其内容包括布桩形式，单桩竖向承载力及复合地基承载力的确定以及下卧层与沉降变形的验算。指出了施工中应注意的事项和应通过的质量检验项目，并通过工程实例进行了验证。     

Learning to Perceive and Act by Trial and Error

This article considers adaptive control architectures that integrate active sensory-motor systems with decision systems based on reinforcement learning. One unavoidable consequence of active perception is that the agent's internal representation often confounds external world states. We call this phoenomenon perceptual aliasingand show that it destabilizes existing reinforcement learning algorithms with respect to the optimal decision policy. We then describe a new decision system that overcomes these difficulties for a restricted class of decision problems. The system incorporates a perceptual subcycle within the overall decision cycle and uses a modified learning algorithm to suppress the effects of perceptual aliasing. The result is a control architecture that learns not only how to solve a task but also where to focus its visual attention in order to collect necessary sensory information.     

On the learning control of a robot manipulator

This paper derives a learning control law to achieve trajectory following for a robot manipulator. The controller consists of two parts, a computed torque servo for the rigid body terms that can be modelled and a learning law for the unmodelled dynamics. An advantage of this method is that bounds can be assigned to the position and velocity tracking errors.