改进的最小二乘法在水文分析计算中的应用

在水分析计算中，经常涉及到变量之间的线性或非线性拟合，而在拟合各种特性曲线时，通常应用以实测资料与拟合曲线间的误差平方和最小作为目标函数的方法——最小二乘法，但这种方法忽视了所有实测点应与拟合曲线间的相对误差尽量不超过某一百分比的原则，为了达到上述要求，提出了非线性的加权最小二乘法及线性相关方程的最小距离平方和法，探讨改进了传统的最小二乘法达到优化的效果。最小距离平方和法与常用的图解法相比，本法所得成果较为客观；与传统的单方向(x或y方向)最小二乘回归法相比，所求线性方程不会因坐标系的选取而改变。最后应用算例进行了初步讨论。     

宽带接入用户认证技术分析与比较

给出了一个宽带接入用户认证系统的基本模型，并基于此模型对目前被广泛应用的PPPoE、WEB、DHCP等用户认证技术进行了分析与比较。最后，简单介绍了用户认证技术的新成员-802．1x(Port Based Network Access Control Protoco1)协议。     

巴彦浩特盆地火成岩的综合地球物理解释

采用综合地球物理方法识别巴彦浩特盆地火成岩,首先利用高精度重磁资料和大地电磁测深资料,初步确定火成岩的平面位置和深度,然后利用钻遇火成岩的已知测井资料,建立人工合成地震记录,在地震剖面上标定出火成岩并分析其波组特征,采用BP神经网络进行火成岩的精细识别.研究表明,综合地球物理解释是提高反演解释精度的有效途径.     

兰州数字遥测地震台网信号传输方式的设计

介绍了地震信号传输的常用方式及各自的优缺点，提出了数字遥测地震台网信号传输方式设计的总原则和基本原则。实际应用表明，兰州数字遥测地震台网信号传输方式的是符合要求的，提出的数字遥测地震台网信号传输方式的总原则和基本原则，对数字遥测地震台网建设有直接的借鉴作用。     

岩体三维不连续裂隙网络及其逆建模方法

通过拟合实测的二维裂隙编录图和钻孔裂隙编录图，优化裂隙三维大小和密度参数，使模型能够准确再现野外所观测到的实际现象，包括开挖面和钻孔上不同裂隙的数量、密度和长度，通过计算实例验证了方法的可行性。     

基于遥感与GIS的20世纪90年代中国城镇用地时空特征

文章利用20世纪90年代初期、中期和末期全国1:100000土地利用动态变化数据提取城镇用地动态变化数据,利用单元自动机和人工神经网络模型对全国城镇用地进行了区划.在此基础上,研究了90年代两个阶段中国城镇用地时空格局.研究表明:90年代前5年东部沿海地区受经济高速发展和开放政策的影响,城镇用地扩展迅速,中西部地区城镇用地扩展较慢;90年代后5年国家加大了耕地资源保护力度,在政府宏观调控政策和耕地资源保护条例的影响下,东部沿海地区城镇用地扩展大幅回落,中部地区城镇扩展也有较大幅度回落,西部地区随着经济发展加快,城镇用地扩展回落较小.     

Seismic risk assessments and GIS technology: applications to infrastructures in the Friuli–Venezia Giulia region (NE Italy)

This paper illustrates the seismic risk preliminary estimates of two different groups of structures located on the territory of the Friuli–Venezia Giulia region (NE Italy) : the first group includes some special industrial plants, and the second group includes bridges and tunnels belonging to the regional highway network. The part of the study on special industrial plants tries to evaluate the degree of expected damage, taking into account their structural typology and ground shaking expressed in terms of macroseismic intensity. The second part of the study is an application of the HAZUS methodology to the tunnels and bridges of a highway network: the combination of expected ground shaking and the construction characteristics lead to very different risk levels, especially when considering the bridges. The resulting damage levels to bridges and tunnels are still only indicative because of the fragility curves used in the evaluations: they were developed for existing bridge and tunnel structural typologies in the U.S.A. Moreover, both examples show the power of GIS technology in storing, elaborating, and mapping spatial data. Copyright © 2003 John Wiley & Sons, Ltd.     

大庆徐家围子地区深部致密砂砾岩气层识别

大庆徐家圈子地区深部致密砂砾岩储层的骨架成分除了含有石英、长石外，还含有许多酸性喷发岩，而且各种骨架成分的含量随深度变化比较大；复杂的岩性使得气的影响被岩性的影响所淹没，从而造成常规气层识别方法失效。针对这一问题，应用神经网络方法准确求取地层颗粒密度和泥质含量，然后对中子和密度测井值进行岩性影响校正和泥质影响校正，使得求出的中子和密度孔隙度仅受地层气的影响，最后将得到的中子和密度孔隙度进行对比，应用中子和密度孔隙度的差异识别气层。     

Landslide susceptibility analysis using GIS and artificial neural network

The purpose of this study is to develop landslide susceptibility analysis techniques using an arti?cial neural network and to apply the newly developed techniques to the study area of Yongin in Korea. Landslide locations were identi?ed in the study area from interpretation of aerial photographs, ?eld survey data, and a spatial database of the topography, soil type and timber cover. The landslide‐related factors (slope, curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter) were extracted from the spatial database. Using those factors, landslide susceptibility was analysed by arti?cial neural network methods. The landslide susceptibility index was calculated by the back‐propagation method, which is a type of arti?cial neural network method, and the susceptibility map was made with a geographic information system (GIS) program. The results of the landslide susceptibility analysis were veri?ed using landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide location. A GIS was used to ef?ciently analyse the vast amount of data, and an arti?cial neural network to be an effective tool to maintain precision and accuracy. The results can be used to reduce hazards associated with landslides and to plan land use and construction. Copyright © 2003 John Wiley & Sons, Ltd.     

A neural network approach for structural identification and diagnosis of a building from seismic response data

This work presents a novel procedure for identifying the dynamic characteristics of a building and diagnosing whether the building has been damaged by earthquakes, using a back‐propagation neural network approach. The dynamic characteristics are directly evaluated from the weighting matrices of the neural network trained by observed acceleration responses and input base excitations. Whether the building is damaged under a large earthquake is assessed by comparing the modal parameters and responses for this large earthquake with those for a small earthquake that has not caused this building any damage. The feasibility of the approach is demonstrated through processing the dynamic responses of a five‐storey steel frame, subjected to different strengths of the Kobe earthquake, in shaking table tests. Copyright © 2002 John Wiley & Sons, Ltd.