一种新的基于PCA变换多源遥感影像像素级融合方法

在多源遥感影像融合中,基于传统PCA变换的多源遥感影像融合的光谱分辨率受到较大影响。提出了一种新的基于PCA变换的多源遥感影像像素级融合方法,通过在传统PCA变换融合算法基础上引入小波变换融合,保留了多波段遥感图像光谱特性的有用信息,进一步提高融合后遥感影像的效果。给出实验的融合结果,并与传统PCA变换方法进行对比,证明了该方法的有效性。     

航空重力数据谐波小波滤波中卷积运算的处理

数据的滤波提取是航空重力测量数据处理的一个重要环节。谐波小波滤波器在频域具有良好的盒形谱特征,可以较好地实现信号的滤波。但谐波小波滤波器是一个连续函数,航空重力测量采集的信号是离散的,无法直接进行卷积运算。讨论了谐波小波用于航空重力数据滤波处理时的卷积运算处理方法,给出了谐波小波频域卷积的算法实现过程和仿真算例。     

利用Grads软件绘制离散点要素等值线

介绍了用Grads软件绘制离散点气象要素等值线的方法以及Grads软件地图文件的存储格式,并以绘制长治地区雨量等值线图为例, 介绍了用Grads软件绘制离散点要素等值线的具体实现过程和脚本程序原代码.     

地磁Z分量低点时间季节性变化研究

通过小波分析和频谱分析,发现Z分量低点时间的小波变换结果曲线(α=6)明显地随节气而变化;对地磁Z分量低点时间季节性变化进行了初步的比较分析.     

基于小波分析的场地波速测量方法

在场地波速测量中,由于噪声等因素的影响很难准确识别P、S波的初至时刻,致使波速结果存在很大的误差。本文给出了一种基于小波变换的波速测量的新方法。该方法利用波动信号的小波变换与弹性波群速度的关系准确识别弹性波初至时刻。弹性波小波变换的峰值时刻代表着以群速度传播的弹性波的初至时刻,使P波、S波的初至时刻的确定具有明确的物理意义,波速的结果准确、可靠、稳定。此外,波动信号的小波多尺度分析还可以确定地层中传播的弹性波的频散特性。最后,该方法在场地波速测量的实测信号的应用表明该方法可准确确定P、S波速。     

Morlet 小波用于环境激励下的模态参数识别研究

本文分别从卷积和Parseval定理的角度推导了非正交小波变换系数的实用计算方法。在环境激励下以互相关函数代替系统的自由响应数据,给出了基于Morlet小波变换的频率、阻尼比的参数识别方法,重点介绍了基于最小二乘法的振型识别技术。采用2层楼仿真算例和潮白河桥应用实例验证本算法,识别结果表明基于Morlet小波变换的模态参数识别技术能够有效地识别出环境激励下系统的模态参数。     

A coupled discrete element model for the simulation of soil and water flow through an orifice

Soil erosion around defective underground pipes can cause ground collapses and sinkholes in urban areas. Most of these soil erosion events are caused by fluidization of the surrounding soil with subsequent washing into defective sewer pipes. In this study, this soil erosion process is simplified as the gradual washout of sand particles mixed with water through an orifice. The discrete element method is used to simulate the large deformation behavior of the sand particles, and the Darcy fluid model is coupled with this approach to simulate fluid flow through porous sand media. A coupled 3D discrete element model is developed and implemented based on this scheme. To simulate previous experiments using this coupled model considering the current computing capacity, we incorporated a ‘supply layer’ to study the continuous erosion process. The coupled model can predict the erosion flow rates of sand and water and the shape of erosion void. Thus, the model can be used as an effective and efficient tool to investigate the soil erosion process around defective pipes. Copyright © 2017 John Wiley & Sons, Ltd.     

Stage level,volume and time‐frequency information content of Lake Tana using stochastic and wavelet analysis methods

Lake Tana is the largest fresh water body situated in the north‐western highlands of Ethiopia. In addition to its ecological services, it serves for local transport, electric power generation, fishing, recreational purposes, and source of dry season irrigation water supply. Evidence shows that the lake has dried at least once at about 15,000–17,000 before present owing to a combination of high evaporation and low precipitation events. Past attempts to understand and simulate historical fluctuation of Lake Tana based on simplistic water balance approach of inflow, outflow, and storage have failed to capture well‐known events of drawdown and rise of the lake that have happened in the last 44 years. This study tested different stochastic methods of lake level and volume simulation for supporting Lake Tana operational planning decision support. Three stochastic methods (perturbations approach, Monte Carlo methods, and wavelet analysis) were employed for lake level and volume simulation, and the results were compared with the stage level measurements. Forty‐four years of daily, monthly, and mean annual lake level data have shown a Gaussian variation with goodness of fit at 0.01 significant levels of the Kolmogorov–Smirnov test. The stochastic simulations predicted the lake stage level of the 1972, 1984, and 2002/2003 historical droughts 99% of the time. The information content (frequency) of fluctuation of Lake Tana for various periods was resolved using Wigner's Time‐Frequency Decomposition method. The wavelet analysis agreed with the perturbations and Monte Carlo simulations resolving the time (1970s, 1980s, and 2000s) in which low frequency and high spectral power fluctuation has occurred. The Monte Carlo method has shown its superiority for risk analysis over perturbation and deterministic method whereas wavelet analysis reconstructed historical record of lake stage level at daily and monthly time scales. Copyright © 2012 John Wiley & Sons, Ltd.     

Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers

Abstract

The study of sediment load is important for its implications to the environment and water resources engineering. Four models were considered in the study of suspended sediment concentration prediction: artificial neural networks (ANNs), neuro-fuzzy model (NF), conjunction of wavelet analysis and neuro-fuzzy (WNF) model, and the conventional sediment rating curve (SRC) method. Using data from a US Geological Survey gauging station, the suspended sediment concentration predicted by the WNF model was in satisfactory agreement with the measured data. Also the proposed WNF model generated reasonable predictions for the extreme values. The cumulative suspended sediment load estimated by this model was much higher than that predicted by the other models, and is close to the observed data. However, in the current modelling, the ANN, NF and SRC models underestimated sediment load. The WNF model was successful in reproducing the hysteresis phenomenon, but the SRC method was not able to model this behaviour. In general, the results showed that the NF model performed better than the ANN and SRC models.

Citation Mirbagheri, S. A., Nourani, V., Rajaee, T. & Alikhani, A. (2010) Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers. Hydrol. Sci. J. 55(7), 1175–1189.