储层敏感性快速预测软件在大港油田的研究与应用

在储层特征分析，室内实验，机理研究的基础上，利用人工神经BP网络建立预测模型，并编制了预测储层5种敏感性的软件，该软件受人为因素干扰小，所需参数少，准确度高，综合符合率大于80％现场应用结果表明，该技术能为制定保护油气层技术措施提供较可靠的依据，能提高油田滚动开发效益，改善老油田的开发效果，该软件对BP算法进行了改进，（1）从两方面入手使网络摆脱平坦区，一是对输入数据进行归一化处理，使O1的取值在[0,1]之间，二是一旦网络陷入平坦区域，局部极小，使连接权值Wkj,Wji和阈值Qk,Qj同时缩小一个因子，λ＞1，可使Ok(1-Ok)脱离零值，离开平坦区；（2）加速收敛，方法有自动调整学习因子，添加动量项以及对权值进行批处理，用BP算法预测储层潜在敏感性，首先应确定影响储层敏感性的主要因素，然后根据这些因素有针对性地收集有关资料并进行处理，再根据敏感性预测的要求，设计相应的网络结构进行训练，最后对训练好的网络进行.检验。     

根据人工裂缝特征优化油井压裂地质方案

近年来大庆油田外围地区地质储量得到动用，每年依靠压裂投产的井逐渐增多，由达西定律可知，在油层厚度一定的情况下，措施井的渗透率是影响产量的关键参数，油井压裂可以改善油井周围地层渗透性，消除近井地带油层污染，从而提高油井产能，而人工压裂的成功与否主要取决于裂缝的导流能力和裂缝的几何形态，为此，根据台105地区地质特征，结合低渗透油田开发实际，本着经济有效的开发原则，从人工裂缝特征，方位对开发效果的影响等方面，论述了优化油井压裂地质方案技术的方法，改善了低渗透油田的开发效果。     

Quantitative analysis of Ni effect on CCT diagrams of novel air-cooled bainite steels using artificial neural network models

The quantitative effect of Ni content on continuous cooling transformation （CCT） diagrams of novel air-cooled bainite steels was analyzed using artificial neural network models. The results showed that Ni may retard the high- and medium-temperature transformation and martensite transformation. The results conform to the materials science theories.     

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.     

Wavefront reduction using graphs,neural networks and genetic algorithm

This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.     

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。     

日本地震简介和日建设计的抗震设计

为更好地帮助读者理解本刊各篇论文的内容,本文简要介绍日本的地震状况,日建设计对地震设计的考虑方法,以及日建设计的设计用人工模拟地震波。     

铝导电轨型材生产工艺研究

研究了6101-T6合金铝导电轨型材的生产工艺，着重研究了化学成分，不同的淬火、时效处理工艺对材料性能的影响。     

人工冻土热工参数智能反演方法研究

首先运用遗传算法,在一定的初边值条件下通过对比试验实测值与解析解确定出导热系数与比热的函数值α(λ,c,ρ),再利用已确定出的系数α,通过遗传数值法计算值与实测值比较,进而确定出等效导热系数λ与比热c。     

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.