用人工神经网络作地质数据分析

本文提出了利用人工神经网络进行地质数据多变量分析的方法，研究表明，此方法具有精度高、运算速度快、算法简单易于编程等显著特点，是地质数据分析中一有效方法。     

Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.     

高氧化态（Ⅱ─Ⅳ）三核金属簇合物构型的人工神经网络判别方法

本文运用一典型的人工神经网络模型─“反向传播”模型，对高氧化态（Ⅱ─Ⅳ）三核金属簇合物的构型分布进行了分析，得到了较好的分类、预报结果为化合物结构分析提供了新的工具。     

超媒体系统中的人工智能方法

一、什么是超媒体近年来迅速崛起的多媒体(multimedia)技术,是一种使计算机具有交互式地综合处理和管理文字、图形、图象、声音、视频等多种媒体能力的技术,必将使计算机技术发生一     

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。     

色彩心理效应模型在人性化Web导购系统中的搭建与应用

人性化、个性化系统是现代Web商务系统的一个发展趋势,也是人工心理的一个研究方向。本文以服装选购系统为例,对人类情感的重要影响因素之一——色彩心理效应进行了进一步的深入研究。文中首次使用人工神经网络对色彩带来的膨胀紧缩感的心理效应进行数学建模,并且在服装导购系统中进行应用算法的设计和实施,从而实现了一种心理效应由感性描述到理性模型的转化,同时也使人性化、个性化智能系统的理念得到进一步完善。实验结果表明此数学模型能够较好的模拟色彩给人带来的膨胀紧缩感,在系统中的应用效果也收到了用户的好评。     

An immune oriented multi-agent system for biological image processing

In this article, we present a parallel image processing system based on the concept of reactive agents. Our system lies in the oRis language, which allows to describe finely and simply the agents’ behaviors to detect image features. We also present a method of segmentation using a multi-agent system, and two biological applications made with oRis. The stopping of this multi-agent system is implemented through a technique issued from immunology: the apoptosis.     

Ethical issues concerning expert systems' applications in education

This article traces the connection between expert systems used as consultants in medicine and their design for instructional purposes in education. It is suggested that there are important differences between these applications. Recognizing these differences leads to the view that the development of intelligent computer-assisted instructions (ICAI) should be guided by empirical research into social/psychological consequences and by ethical inquiries into the acceptability of those consequences. Three proposals are put forward: (1) that the pedagogical role of intelligent CAI be clarified, (2) that forms of intelligent CAI be developed that aim primarily at refining rather than replacing human judgements, and (3) that ICAI research and development projects contain components which address ethical and social/psychological components and which are equitably-funded, integral parts of the overall development effort.This work was supported in part by funds from the Foundation of the University of North Carolina at Charlotte and from the State of North Carolina. An earlier version of this paper was read at the Human Dimension in Artificial Intelligence Symposium held at the University of Kentucky (April 1988).     

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.