融合多特征改进型PSPNet模型应用于复杂场景下的建筑物提取

针对复杂场景下高分辨率遥感影像中建筑物提取精度低的问题,本文提出了一种融合多特征改进型PSPNet模型,在PSPNet网络的基础上,加入膨胀卷积模块并融合图像的浅层特征.试验结果表明,融合多特征改进型PSPNet模型的预测结果总体精度为95.90％,建筑物提取精度平均为77.77％,均高于其他模型.其在不同场景上的表现...     

基于相关迭代的非因果匹配滤波器多次波压制方法

针对常规多次波压制(SRME)方法存在的缺陷进行了改进.首先在多次波模型道预测阶段,采用数据相关和迭代更新的策略预测多次波模型道,该方法降低了SRME方法采用数据空间褶积对输入数据要求严格的限制,提高了对近偏移距缺失和空间假频数据的适应性.在匹配相减阶段,本文设计了一种非因果非平稳的匹配滤波器,该滤波器可以对整道多次波模型进行处理,而且当预测多次波模型道滞后于实际多次波时,也能够对多次波模型道进行很好的匹配.模型数据和实际数据试算证明该方法在多次波模型道预测和匹配相减阶段的优越性.     

LIC color texture enhancement algorithm for ocean vector field data based on HSV color mapping and cumulative distribution function

Texture-based visualization method is a common method in the visualization of vector field data. Aiming at adding color mapping to the texture of ocean vector field and solving the ambiguity of vector direction in texture image, a new color texture enhancement algorithm based on the Line Integral Convolution (LIC) for the vector field data is proposed, which combines the HSV color mapping and cumulative distribution function calculation of vector field data. This algorithm can be summarized as follows: firstly, the vector field data is convoluted twice by line integration to get the gray texture image. Secondly, the method of mapping vector data to each component of the HSV color space is established. And then, the vector field data is mapped into HSV color space and converted from HSV to RGB values to get the color image. Thirdly, the cumulative distribution function of the RGB color components of the gray texture image and the color image is constructed to enhance the gray texture and RGB color values. Finally, both the gray texture image and the color image are fused to get the color texture. The experimental results show that the proposed LIC color texture enhancement algorithm is capable of generating a better display of vector field data. Furthermore, the ambiguity of vector direction in the texture images is solved and the direction information of the vector field is expressed more accurately.     

改进Mask R-CNN公路病害检测算法

针对公路路面病害与背景像素对比度低导致检测困难的问题,本文提出了改进Mask R-CNN公路病害检测算法(FAC-Mask R-CNN)。首先在ResNet101基础上增加强位置信息浅层特征表达,并融合相邻特征图作为主干网络最终特征输出,同时引入CBAM模块,以减弱目标与背景像素间低对比度的影响;然后采用深度可分离卷积和空洞卷积分别代替主干网络及有效特征层输出过程应用的普通卷积,提升模型计算效率及掩码预测精度。FAC-Mask R-CNN在公路路面病害数据集(RDD)上平均精确率为89.86%,召回率为88.54%,调和均值为90%,相较于Mask R-CNN算法平均精确率提升3.09%。结果表明,FAC-Mask R-CNN能有效完成公路路面病害精细化检测与分割任务。     

Statistical analysis of friction sleeve length effects on soil classification

The cone penetration test (CPT) provides profiles of the tip resistance, sleeve friction, and pore water pressure encountered while penetrating the subsurface. These parameters are used either directly or indirectly to classify the soil types present and to obtain geotechnical design parameters. However, fundamental discrepancies exist in the manner by which these parameters are measured. This paper describes the results of a study that shows the sleeve friction measurement introduces unnecessary redundancy due to the length of the standard friction sleeve compared to the measurement increment. Further, the high sleeve length to measurement increment ratio results in filtering and smoothing of the friction data, thereby causing the variability of the friction between the soil and the cone sleeve to be underestimated. The importance of understanding the role of the sleeve length on measurements is demonstrated using synthetically generated friction profiles and estimating the profiles that would be measured using sleeves of different lengths. Differences in how the soils are classified as a function of the sleeve length used to obtain each profile are illustrated. Solutions are presented to validate the synthetic sleeve friction profiles, to demonstrate the filtering and smoothing effects of the friction sleeve on the data, and to explain the implications of the sleeve length on soil classification. Copyright © 2004 John Wiley & Sons, Ltd.     

图卷积网络在道路网选取中的应用

针对现有制图综合中的道路网自动选取方法不能有效地利用道路网的空间特征问题,该文把道路网抽象为图结构,提出了使用图卷积网络来进行道路网的自动选取,并比较分析了不同的图卷积网络在道路网选取中的适用性。结果表明,图卷积网络可以通过多层卷积来自动提取不同局部范围的空间特征,从而减少空间特征的人工构建,相比传统的多层感知机(MLP)等人工智能选取方法,具有更高的选取精度。对于不同的图卷积网络模型,使用最大池化聚合的GraphSAGE获得了最优的性能。     

A novel residual graph convolution deep learning model for short-term network-based traffic forecasting

ABSTRACT

Short-term traffic forecasting on large street networks is significant in transportation and urban management, such as real-time route guidance and congestion alleviation. Nevertheless, it is very challenging to obtain high prediction accuracy with reasonable computational cost due to the complex spatial dependency on the traffic network and the time-varying traffic patterns. To address these issues, this paper develops a residual graph convolution long short-term memory (RGC-LSTM) model for spatial-temporal data forecasting considering the network topology. This model integrates a new graph convolution operator for spatial modelling on networks and a residual LSTM structure for temporal modelling considering multiple periodicities. The proposed model has few parameters, low computational complexity, and a fast convergence rate. The framework is evaluated on both the 10-min traffic speed data from Shanghai, China and the 5-min Caltrans Performance Measurement System (PeMS) traffic flow data. Experiments show the advantages of the proposed approach over various state-of-the-art baselines, as well as consistent performance across different datasets.     

Simple procedure to simulate karstic aquifers

A procedure to simulate karstic aquifers is presented. It is based on a simulation of spring discharge using precipitation and, where necessary, temperature as input data. The karstic aquifer system is considered to be divided into three zones: the surface zone, the unsaturated zone (UZ) and the saturated zone (SZ). Each of these is described by a transfer function that determines the water supplied from the overlying zone. Water loss through evapotranspiration is calculated empirically and subtracted from the total precipitation in order to obtain the effective infiltration into the UZ. The transfer function characterizing the UZ can be expressed as a convolution function. The UZ acts as a buffer, delaying effective infiltration into the SZ. Water discharge from the SZ is described by the recession function of the spring, and this becomes the transfer function that characterizes the emergence of water from the SZ. The model permits the simulation of the influence of pumped abstractions from the system by a simple modification of the transfer functions involved. Copyright © 2007 John Wiley & Sons, Ltd.     

基于数据一致性预测与压制自由表面多次波--理论研究与试处理

从声波波场理论出发,首先在不考虑自由表面反射的情况下研究了有效波波场传播及反射规律,继而考虑自由表面反射的情况,并详尽推导了压制自由表面多次波的正演和反演数学模型。从物理本质上对自由表面多次波的产生、预测及压制做了深入的剖析,讨论了基于数据一致性时空域褶积的多次波预测方法原理,实现了自由表面相关多次波自适应压制的迭代方法过程。复杂起伏海底的理论模型试算实例表明：在多次波产生系统非常复杂的情况下,本方法仍能非常有效地压制各种与自由表面相关的多次波,同时还能很好地保持有效波的能量,取得了很好的压制多次波效果。     

基于VIIRS数据的油气平台提取技术研究

油气平台作为海上油气资源勘探开发的主要设备之一,其数量与空间分布反映了一个区域油气资源的开发状况。普通光学影像易受天气状况影响,而雷达数据成本较高,这给油气平台的检测带来了一定的困难。由于油气平台作业过程中,需要灯光照明,同时伴气的燃烧也产生很强的灯光,因此可以通过检测灯光来实现油气平台的提取。针对VIIRS数据具有强夜间光探测能力,本文提出了一种卷积运算临界值法对海上油气平台进行提取。首先对2期不同时相的VIIRS数据进行卷积运算,对亮像元进行了增强处理,对背景像元进行弱化处理,从而明确区分疑似目标与背景,然后以0值为分界点,对疑似目标进行提取,最后利用油气平台相对静止的特性,通过邻域分析,实现油气平台的提取。结果表明,本文提出的卷积运算临界值法可以有效地提取油气平台,提取准确率约为85.4%,同时可以有效地减少由于经验阈值对提取结果造成的误差。