山东地磁台网受宁东高压直流输电干扰预处理质量分析

为进一步提高山东地磁台网受高压直流输电干扰的预处理质量,通过中国地震前兆数据处理系统中相对差值检测和预处理检测功能,对山东地磁台网多年来受宁东高压直流输电干扰预处理情况进行了总结分析。结果表明,经过数据预处理,宁东高压直流输电干扰基本被去除,但仍然存在高压直流输电干扰误判、起止时间错判、干扰幅度计量不精确等问题。针对上述问题,对数据进行复核和校对,应用"缓变台阶"功能重新处理,并加强对H、D分量干扰特征的研究。     

镇江地震台网理论监测能力评估

基于近震震级公式,对镇江地震台网理论监测能力进行评估,绘制地震监测能力图,以确定监测区不同地点发生地震时能被台网有效分析和定位的地震最小震级。镇江市句容县在该台网理论监测震级最小,为ML1.2—1.3;在镇江及相邻城市,发生M_L 1.8分析认为,以上地震均能被有效监测。     

混沌理论在桥梁变形监测中的应用

针对桥梁的非线性下沉问题,引用了混沌理论,首先求取时间序列的两重构参数时间延迟τ和嵌入维数m进行相空间重构;随后进行混沌特性判别,确定该时间序列存在混沌迹象;最后根据所求参数建立加权零阶局域预计模型和RBF神经网络混沌预计模型对观测数据进行预计分析,并与系数为0.9的指数平滑预测模型进行比较,结果显示混沌预计模型值更接...     

基于分形理论的航空图像分类方法

提出一种基于分形理论和BP神经网络的航空遥感图像有监督分类方法。该方法尝试将航空图像的光谱信息和纹理特征相结合。它首先将彩色航空图像由RGB格式转化为HSI格式，然后，根据亮度计算分数维、多重分形广义维数谱q-D(q)和“空隙”等基于分形的纹理特征，同时加入归一化的色度和饱和度作为光谱特征，采用BP神经网络作为分类器。通过对彩色航空图像的分类实验，结果证实该方法行之有效。     

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.     

面向对象的城市管网数据组织模型设计

针对现有城市管网数据组织方式存在的问题,提出了一种基于面向对象的城市管网数据组织模型,该模型从人们认知的角度,将客观世界中的管网作为集数据和方法于一体的对象综合体,进行一体化存储和管理。模型在引入"类"概念的基础上,对基类中几何类和实体类的结构进行了详细设计,并讨论了模型中类与类、类与对象之间的关系,最后以城市供水管网为例,设计了基于对象的城市供水管网数据组织模型。     

港珠澳大桥首级控制网复测

介绍了港珠澳大桥首级控制网的复测方案,包括复测精度及网形设计、对控制网复测方法、技术要求及成果精度进行了介绍。最后,通过控制网复测成果和建网成果的比较,对首级控制网建网成果质量及控制点的稳定性进行了分析评价。     

径向基神经网络GPS高程转换方法

针对GPS高程转换问题,给出了基于径向基神经网络转换GPS高程的模型。用实际观测数据对该模型进行了试验,结果表明,用径向基神经网络转换GPS高程精度高于二次拟合法和BP神经网络法。径向基神经网络能够有效克服BP神经网络局部极小值的缺点,并且具有较高的收敛速度,在GPS高程转换方面具有广阔应用前景。     

塔河油田地面工程信息系统的设计与探讨

着重探讨了塔河油田地面工程信息系统的建设思路和实现方法,针对油田的实际,以当前先进的组件式地理信息系统软件MAPGIS和可视化编程工具Microsoft Visual Studio构架的技术体系为基础,开发一套方便实用的油田地面工程信息系统。本系统建设为集原油集输、天然气和油田伴生气集输、道路、输供电线路为一体的可视化数据平台,实现了整个油田数据采集、管线图绘制,以及信息的浏览、查询统计、综合管理等功能。