中国城市体系网络化研究   总被引：14，自引：1，他引：13  

胡国建  陈传明  金星星  王强 《地理学报》2019,74(4):681-693

当前,学者普遍认同城市体系研究的重心从等级范式向网络范式转向。在大量的文献梳理基础上,阐述20世纪80年代以来中国城市体系研究范式的转向过程,并进一步梳理中国城市网络研究的进展、问题与关注重点。结果表明：2010年之后,网络成为中国城市体系研究的主流范式,等级体系文献数量呈波动递减趋势,全国和长三角成为热点关注区域;属性数据一定程度上弥补了早期城市网络研究中数据匮乏的状况,关系数据应成为未来研究的侧重点;不同研究视角及其所应用的数据存在着一定的局限性,多元视角的综合研究成为趋势。在此基础上,提出城市网络研究未来可能的突破点,包括：调整国家城市网络的研究框架、超越交通数据直接考察城市间的实体联系、测度企业外部的横向联系、有向加权网络分析和可视化、增加研究中的地理“意味”等。  相似文献   

SAR image despeckling with a multilayer perceptron neural network     

Xiao Tang  Lei Zhang  Xiaoli Ding 《International Journal of Digital Earth》2019,12(3):354-374

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.  相似文献   

基于卷积神经网的CCTV视频中排水管道缺陷的智能检测     

吕兵  刘玉贤  叶绍泽  闫臻 《测绘通报》2019,(11):103-108

作为地下空间信息测绘工作的一个重要部分，基于排水管道内部测绘信息的管道缺陷检测越来越受到人们的重视。CCTV技术是一种广泛使用的排水管道内部测绘与缺陷检测技术。近些年基于卷积神经网的人工智能技术在图像识别中取得了巨大成功，受此启发，提出了一种基于卷积神经网络的排水管道缺陷的检测方法，以提高CCTV视频中的管道缺陷检测的自动化和智能化。试验证明了该方法的有效性，其在缺陷识别的准确率和召回率及识别速度上均满足了排水管道缺陷智能检测的需要；同时该方法也已经在深圳市的排水管道检测中得到广泛的应用。  相似文献   

最优权组合预测法在采煤沉陷变形预测中的应用   总被引：1，自引：0，他引：1  

鲁小红 《测绘通报》2020,(4):111-115

煤矿地表沉降变形预测多基于煤矿开采沉陷预计理论展开，基于变形分析理论的变形预测模型目前多集中在单模型预测。本文基于组合预测思想，以非等间隔灰色预测模型与BP神经网络模型为预测单模型，以陕西北部某煤矿采煤工作面上方实测地表沉降值为数据源，以最优加权法对单模型预测结果开展了最优权组合，组合模型中两种单模型的权重分别为0.466 7、0.533 3。选取部分监测点的预测结果进行模型精度评价，结果表明：3种预测模型精度均达到了一级。经对比3种模型预测结果，最优权组合预测的模型精度较单模型明显提升，预测结果较非等间隔灰色预测模型与BP神经网络预测模型有明显增益。  相似文献   

基于高分遥感影像的建筑物侧面信息提取及其高度计算     

宋旭东  曹文峰  冯德俊  张星星 《北京测绘》2020,(3):296-300

本文选取成都市某一区域建筑物A、B为研究对象,采用分辨率为0.61 m的Quick bird影像,运用图像分割法和LVQ神经网络算法,提取建筑物侧面信息,根据假设法原理,构建高度计算物理模型,求取建筑物高度。对比实测数据,结合可能影响实验结果的实地因素、遥感影像因素进行精度分析与评价,探讨基于高分遥感影像的建筑物侧面信息提取和高度计算的方法。结果表明,LVQ神经网络算法在建筑物侧面提取和高度计算中有更好的应用价值,精度高达94%。  相似文献   

基于深度学习的目标检测定位系统设计与实现     

王俊强  李建胜  程相博  杨戬峰 《测绘与空间地理信息》2020,(1):133-136,144

针对传统遥感影像目标检测方法效率不高,并且无有效手段对检测信息进行管理利用的问题,提出了在B/S构架下基于深度学习的目标检测及定位方法。通过集成深度学习框架、WebGIS以及数据库,实现了集遥感影像目标检测、展示及管理于一体的目标检测定位系统,满足多用户基于前端浏览器的并发目标检测需求。利用网格划分策略,实现了基于前端的大区域范围的目标快速检测。基于某机场飞机目标及某城市区域运动场目标检测结果表明:本文设计的目标检测定位系统能够在前端实现目标快速检测定位,具有较高检测精度,并可有效管理检测信息,为深度学习循环再利用提供数据支撑。  相似文献   

基于遗传Elman神经网络进行矿区GPS高程拟合     

张志杰  王维兴  王宝山 《测绘与空间地理信息》2020,(4):173-177,181

目前,城市、平原地区的似大地水准面建立精度已经达到厘米级,但在矿区进行高程拟合时,由于地面高低起伏没有规则,其似大地水准面的拟合精度并不理想。针对此问题,本文提出利用遗传算法优化Elman神经网络的方法精化似大地水准面,采用移去-恢复法对残差进行建模,使用EGM 2008地球重力场模型和地形起伏信息来精化求解似大地水准面和参考椭球面之间的高程异常,同时着重分析了地球重力场模型以及地形变化信息对高程异常求解的重要性,并使用某矿区实测数据(GPS、水准)对所提方法进行验证,实验结果表明:文中所提方法的精度要优于二次曲面拟合模型和单一Elman模型,其外符合精度达到了1.14 cm,可以代替四等水准测量。  相似文献   

Analysis of resistance factors for LRFD of soil nail pullout limit state using default FHWA load and resistance models     

Hui Hu 《Marine Georesources & Geotechnology》2020,38(3):332-348

Abstract

Resistance factors for load and resistance factor design (LRFD) of pullout limit state of both permanent and temporary soil nails are calibrated against a wide design space using the current Federal Highway Administration (FHWA) nail load and resistance models. The calculated resistance factors were shown to scatter broadly among design scenarios that differ in wall face batter, soil friction angle, nail ultimate bond strength, and surcharge live load. An important lesson learned from the analysis results is that the current practice of using a single resistance factor for LRFD of nail pullout limit state could not result in uniform reliabilities across different design scenarios. Simple artificial neural network (ANN) models were developed for computation of resistance factors. Design examples demonstrated the ability of the ANN models in providing resistance factors that yield satisfactory and consistent reliabilities in different nail pullout designs.  相似文献   

Inference of in situ stress from thermoporoelastic borehole breakouts based on artificial neural network     

Hua Zhang  Shunde Yin 《国际地质力学数值与分析法杂志》2019,43(16):2493-2511

The determination of in situ stresses is very important in petroleum engineering. Hydraulic fracturing is a widely accepted technique for the determination of in situ stresses nowadays. Unfortunately, the hydraulic fracturing test is time-consuming and expensive. Taking advantage of the shape of borehole breakouts measured from widely available caliper and image logs to determine in situ stress in petroleum engineering is highly attractive. By finite element modeling of borehole breakouts considering thermoporoelasticity, the authors simulate the process of borehole breakouts in terms of initiation, development, and stabilization under Mogi-Coulomb criterion and end up with the shape of borehole breakouts. Artificial neural network provides such a tool to establish the relationship between in situ stress and shape of borehole breakouts, which can be used to determine in situ stress based on different shape of borehole breakouts by inverse analysis. In this paper, two steps are taken to determine in situ stress by inverse analysis. First, sets of finite element modeling provide sets of data on in situ stress and borehole breakout measures considering the influence of drilling fluid temperature and pore pressure, which will be used to train an artificial neural network that can eventually represent the relationship between the in situ stress and borehole breakout measures. Second, for a given measure of borehole breakouts in a certain drilling fluid temperature, the trained artificial neural network will be used to predict the corresponding in situ stress. Results of numerical experiments show that the inverse analysis based on finite element modeling of borehole breakouts and artificial neural network is a promising method to determine in situ stress.  相似文献   

渤海海域浮游病毒和浮游细菌的丰度变化与环境因子之间的耦联关系     

王彩霞  吴霖  王毅波  Paterson James S.  Mitchell James G.  胡晓珂 《海洋学报(英文版)》2020,39(6):72-83

Uncovering the role of environmental factors and finding critical factors which harbor significant fractions in governing microbial communities remain key questions in coastal marine systems. To detect the interactions between environmental factors and distributions of virio-and bacterioplankton in trophic coastal areas, we used flow cytometry to investigate the abundance of virio-and bacterioplankton covering 31 stations in the Bohai Sea of China. Our results suggested that the average abundance of total virus(TV) in winter(～2.29×10~8 particles/mL)was slightly lower than in summer(～3.83×10~8 particles/mL). The mean total bacterial abundance(TB) was much lower in winter(～2.54×107 particles/mL) than in summer(～5.43×10~7 particles/mL). Correlation analysis via redundancy analysis(RDA) and network analysis among virioplankton, bacterioplankton and environmental factors revealed that the abundances of viral and bacterial subpopulations depend on environmental factors. In winter, only temperature significantly influenced the abundances of virio-and bacterioplankton. In summer, in addition to temperature, both salinity and nutrient(SiO_2) had a remarkable impact on the distribution of virioand bacterioplankton. Our results showed a clear seasonal and trophic pattern throughout the whole water system, which revealed that temperature and eutrophication may play crucial roles in microbial distribution pattern.  相似文献