综合应用地震属性、测井数据反演储层参数

本文研究了样点地震属性的特征提取，利用BP神经网络建立测井声波时差和地震属性的非线性映射关系。采用距离加权平均对研究区所有井的反演结果进行外推。为了提高分辨率和计算结果的准确性，详细分析、研究了适合于地震信号分解和重构的小波，以及测井声波时差和地震波阻抗与层界面的关系。最后，对反演的声波时差资料进行界面影响校正，进而计算出较符合实际情况的孔隙率参数。经已知井和新钻井验证，计算结果和实际情况相一致，效果令人满意。     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

SMS——智能网的业务管理系统

本文叙述了智能网的业务管理系统所实现的３种功能：业务管理功能，网络管理功能和业务管理访问功能，还介绍了业务管理和网络管理之间的关系，ＳＭＳ的集中式和分布式两种体系结构及业务管理功能的设计方法和进一步研究方向。     

Using neural networks to learn hand-eye co-ordination

The work presented in this paper shows how the association of proprioceptive and exteroceptive stimuli can enable a Kohonen neural network, controlling a robot arm, to learn hand-eye co-ordination so that the arm can reach for and track a visually presented target. The approach presented in this work assumes no a priorimodel of arm kinematics or of the imaging characteristics of the cameras. No explicit representation, such as homogeneous transformations, is used for the specification of robot pose, and camera calibration and triangulation are done implicitly as the system adapts and learns its hand-eye co-ordination by experience. This research is validated on physical devices and not by simulation.     

Neural networks for contract bridge bidding

The objective of this study is to explore the possibility of capturing the reasoning process used in bidding a hand in a bridge game by an artificial neural network. We show that a multilayer feedforward neural network can be trained to learn to make an opening bid with a new hand. The game of bridge, like many other games used in artificial intelligence, can easily be represented in a machine. But, unlike most games used in artificial intelligence, bridge uses subtle reasoning over and above the agreed conventional system, to make a bid from the pattern of a given hand. Although it is difficult for a player to spell out the precise reasoning process he uses, we find that a neural network can indeed capture it. We demonstrate the results for the case of one-level opening bids, and discuss the need for a hierarchical architecture to deal with bids at all levels.     

无线传感器网络MAC层协议的对比研究

无线传感器网络是二十一世纪新兴的网络技术，它的出现使网络的发展进入一个新的阶段。针对无线传感器网络MAC层协议的研究一直是人们普遍关注的问题。总结了近年来的研究成果并针对TDMA，IEEE802．15．4，S—MAC，T—MAC几种典型的MAC层协议进行了对比分析，根据其各自的优点提出将来工作的方向和建议。     

Estimation of fouling in a plate heat exchanger through the application of neural networks

Pasteurization is an important, if not the most important, process step in the packaging of milk. It is subject to alterations stemming from the variation in the temperature, pH and raw milk quality. The variability may manifest itself in changes in the formation of the deposit (fouling) in the pasteurization unit, such that there is a need for tools, both instrumentation and computational, to help in monitoring the process and keeping it on the desired course. In this paper we describe a practical procedure based on artificial neural networks (ANN) that allows prediction of the deposit thickness, the overall heat transfer coefficient and the critical time (the time that the unit has to be stopped for cleaning) for reducing the impact of fouling on such processes. The procedure determines when the cleaning operation is required once the system is under critical conditions of operations. A combination of fundamental studies and plant measurements were used for study of the operating conditions and thus evaluation of the trades‐offs between operating conditions and longer operating life span. The results are encouraging, enough to validate current operating industrial techniques. Copyright © 2005 Society of Chemical Industry     

Pancyclicity of recursive circulant graphs

In this paper, we study the existence of cycles of all lengths in the recursive circulant graphs, and we show a necessary and sufficient condition for the graph being pancyclic and bipancyclic.     

Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction

This paper introduces and evaluates a new class of knowledge model, the recursive Bayesian multinet (RBMN), which encodes the joint probability distribution of a given database. RBMNs extend Bayesian networks (BNs) as well as partitional clustering systems. Briefly, a RBMN is a decision tree with component BNs at the leaves. A RBMN is learnt using a greedy, heuristic approach akin to that used by many supervised decision tree learners, but where BNs are learnt at leaves using constructive induction. A key idea is to treat expected data as real data. This allows us to complete the database and to take advantage of a closed form for the marginal likelihood of the expected complete data that factorizes into separate marginal likelihoods for each family (a node and its parents). Our approach is evaluated on synthetic and real-world databases.     

两相电流互感器配电网零序电流构造方法

中性点非直接接地配电网大多只安装A，C两相电流互感器（TA），而现有单相接地故障选线方法基本都以零序电流为基础实现。如何在两相TA配电网中准确检测并隔离接地故障线路，成为长期困扰实际运行的技术难题。通过对暂态电流的频域和时域分析，找出B相暂态电流与A，C相暂态电流的对应关系，提出在A相和C相接地时由A相和C相暂态电流构造B相暂态电流，进而得到较精确零序电流的方法。通过大量仿真实验验证了所提出的构造方法的正确性。零序电流的成功构造为实现两相TA配电网单相接地故障选线提供了基础。