中原城市群公路网络建设与城市化水平相关性研究

分析了中原城市群地区1994～2004年公路交通网络和城市化的发展及现状,寻求区域内公路网络发展和城市化水平相关性,得出二者无论是在时间序列还是在空间系列上都具有显著的线性相关性.证明陈彦光提出的线性相关模型不仅可应用于铁路交通网络分析,而且还能适用于公路交通网络分析.在市场经济条件下,交通网络与城市化是同步发展、相互促进的,且相关性更强.     

基于神经网络的滑移隔震结构智能半主动控制

考虑上部结构的刚度和阻尼,使用神经网络控制算法计算基底摩擦力的大小,研究了滑移隔震结构的半主动控制。对计算实例的分析表明,通过半主动控制的滑移隔震结构不但具有较好的隔震效果,且能有效地减小基底的最大滑移量及残余位移。为对比各种控制方法的控制效果,文中还利用Bang-Bang控制和瞬时最优控制算法对滑移隔震结构进行了半主动控制。对比分析表明,基于神经网络控制算法的控制效果优于其它控制算法,具有反馈量少,稳健性强等特点。     

网络计划管理技术在长江某穿越隧道工程中的应用

网络计划技术是一种科学的计划管理技术，它对工程组织过程和项目实施步骤进行全面的规划、编排，并在工程项目实施初期对多种方案进入深入的研究与比较，更科学地进行目标进度的安排。本文以长江某穿越隧道工程为例，详细探讨了用网络计划技术进行工程管理的过程。     

水库群优化调度函数的人工神经网络方法研究

提出了研究水库群优化调度函数的人工神经网络方法,并探讨了神经网络的训练参数、训练方法和训练样本的改变对网络训练和应用效果的影响。实例研究表明,模型及其算法是可行的、有效的。     

亚洲中东部岩石圈塑性流动网络与构造应力场

:板块边缘驱动作用主要通过岩石圈下层的网络状塑性流动实现其向板内的远程传递 ,并控制上层的构造变形。相应地造成构造应力场的的多层分布格局 ,主要包括下层 (含下地壳和岩石圈地幔 )、多震层 (属于上部地壳 )和浅层 (浅表地壳 )应力场。这些层中最大压应力方向可分别采用塑性流动网络共轭角平分线、震源机制解和井孔应力测量等方法加以确定。根据对亚洲中—东部下层与多震层应力场的对比表明 ,大部分地区二者的应力方向基本一致 ,表明了下层对上层的控制 ,这对了解板内应力场的一般趋势与格架提供了基础。靠近驱动边界的局部地段 ,由于上部地壳直接的传递作用 ,往往导致上、下层应力方向的显著偏差 ,有可能成为进一步了解深浅层联系和差异的一种方法     

叠前正演模拟与偏移的网络并行计算

在叠前深度偏移和非零炮检距声波方程正演计算过程中包含了大量的可并行计算的成分。作者在本文中提出叠前正演模拟与偏移的网络并行计算算法，并基于TCP／IP协议，将该算法设计成网络并行处理程序，极大地提高了计算效率。实际运算结果证明，本文提出的并行算法和技术路线是切实可行的。     

The introduction of neural network system and its applications in rock engineering

The neural network system has been developing very fast recently. It has been widely used in many industries such as automation, nuclear power plant, chemical industry, etc. Neural network systems have a great advantage in dealing with problems in which many factors influence the process and result, and the understanding of this process is poor, and there are experimental data or field data. In rock engineering, many problems are of this nature. In this paper, a brief introduction to neural network systems is given. Problems such as what is a neural network, how it works and what kind of advantages it has are discussed. After this, several applications in rock engineering, made by us, are presented. Case 1 is ore boundary delineation. In this case, the rock are divided into three classes, i.e.: (1) waste rock; (2) semi-ore; and (3) ore for mining purposes. The neural network system built can judge whether it is ore, semi-ore or waste rock along the borehole according its corresponding geophysical logging data, such as gamma-ray, gamma-gamma, neutron and resistivity. Case 2 is aggregate quality prediction. In this case, the quality parameters: (1) impact value; (2) abrasion value I; and (3) abrasion value II are predicted by using a neural network system based on density, point load, content of quarts and content of brittle minerals. Case 3 is rock indentation depth prediction. In this case, the rock indentation depth under indentation load is predicted by the established neural network system based on the indentation load on rock, indenter type and rock mechanical properties, such as uniaxial compressive strength, Young's modulus. Poisson's ratio, critical energy release rate and density. In all these cases, the neural network systems have been applied successfully. The testing results are satisfactory and better than the existing techniques.     

Texture Segmentation Based on Image Model and Neural Network

INTRODUCTIoNImagetextureanalysisisanimportantpartofresearchin-tocomputervision.Forobjectidentificationandunderstand-ing,textureanalysisisthebasisoftheresearchwork.Ingeneral,texturecanberegardedasakindofstructurethatconsistsofmanytextureelementsorpatternswhicharemoreorlesssimilar,i.e.,primitivesthatformtexturesandspatialdependenceorinteractionbetweentheprimitives.Ex-tensiveresearchhasbeendoneintextureanalysis,andrefer-ence(Haralick,l979)hasmadeathoroughsurvey.Amongthesetextureanalysismetho…     

Channelized and hillslope sediment transport and the geomorphology of mountain belts

This paper uses the results of landscape evolution models and morphometric data from the Andes of northern Peru and the eastern Swiss Alps to illustrate how the ratio between sediment transport on hillslopes and in channels influences landscape and channel network morphologies and dynamics. The headwaters of fluvial- and debris-flow-dominated systems (channelized processes) are characterized by rough, high-relief, highly incised surfaces which contain a dense and hence a closely spaced channel network. Also, these systems tend to respond rapidly to modifications in external forcing (e.g., rock uplift and/or precipitation). This is the case because the high channel density results in a high bulk diffusivity. In contrast, headwaters where landsliding is an important sediment source are characterized by a low channel density and by rather straight and unstable channels. In addition, the topographies are generally smooth. The low channel density then results in a relatively low bulk diffusivity. As a consequence, response times are greater in headwaters of landslide-dominated systems than in highly dissected drainages. The Peruvian and Swiss case studies show how regional differences in climate and the litho-tectonic architecture potentially exert contrasting controls on the relative importance of channelized versus hillslope processes and thus on the overall geomorphometry. Specifically, the Peruvian example illustrates to what extent the storminess of climate has influenced production and transport of sediment on hillslopes and in channels, and how these differences are seen in the morphometry of the landscape. The Swiss example shows how the bedding orientation of the bedrock drives channelized and hillslope processes to contrasting extents, and how these differences are mirrored in the landscape. An erratum to this article can be found at     

裂隙网络模拟与REV尺度研究

研究了利用平面四边形模拟节理岩体三维裂隙网络的方法。在生成裂隙网络时,同时考虑结构面几何参数和力学参数的随机性。利用裂隙网络研究了确定岩体REV尺度的指标。在此基础上,编制了岩体裂隙网络模拟程序、裂隙网络图形输出程序和岩体REV尺度指标分析程序。通过算例分析,验证了研究成果及程序的合理性,并得出了岩体REV尺度约为各组裂隙中最大迹长期望值3~4倍的结论。研究成果为后续计算岩体等效力学参数奠定了基础。