内蒙古翁公敖包航磁异常的推断与解释          下载免费PDF全文

郭玉峰  张鹏  万佳宇  黄金辉  田华  田亮  李乐 《地质找矿论丛》2018,33(4):634-638

文章对内蒙古四子王旗—土默特右旗中北部近年发现的翁公敖包航磁异常进行推断与解释,在对找矿有望的航磁异常进行筛选后,对翁公敖包航磁异常进行了野外地质-地球物理查证,确定异常为铁矿所致;采用向上延拓、垂向导数、斜导数及小波变换等方法对航磁异常进行数据转换处理,以获取铁矿体的横向及纵向分布信息,取得了较好的效果。  相似文献   

基于小波分析与Mann-Kendall法的岩溶大泉动态研究   总被引：1，自引：1，他引：0  

迟光耀  邢立亭  侯新宇  黄林显  杨奕  张文静 《中国岩溶》2018,37(4):515-526

研究地下水动态是认识地下水资源的有效手段。根据1956－2013年济南岩溶泉域大气降水及地下水水位动态监测资料,采用小波分析法、Mann-Kendall趋势检验、突变检验法研究了58个水文年泉水位对大气降水的响应,可以看出:（1）大气降水和泉水位呈现出多尺度的变化特征,长时间尺度上两者的变化周期基本相同,变化周期为16年和12年,说明大气降水对泉水位有直接影响;（2）在1956—2013年,济南泉域地下水水位具有0.65 m·（10a）-1的年际显著下降趋势,但降水具有12.65 mm·（10a）-1的不显著上升趋势,说明在人为因素影响下泉水动态的影响因素的权重发生了变化;（3）大气降水在1999年发生突变,1999年之后年降水为增加趋势;而地下水水位突变年份为1967年,1967年以后水位持续降低,2004年以后水位快速上升,泉水位未来趋势应与降水保持一致,呈上升趋势,说明大气降水并非泉水动态的唯一影响因素;（4）通过建立不同时段的多元回归模型,表明近58年来地下水水位的主要影响因素由大气降水到人工开采之间的转换,同时验证了小波分析和Mann-Kendall法研究地下水动态的适宜性和可靠性,也为济南市的保泉提供了参考依据。   相似文献   

磁法三维建模在龙王沟磁铁矿勘探中的应用     

陈炳锦 《地质与勘探》2021,57(1):146-155

以龙王沟磁铁矿高精度磁测数据为基础,采用小波多尺度分解方法,对化极后的磁法数据进行多尺度分解,通过功率谱法计算小波多尺度分解后的各阶细节异常的场源深度。结合地形、地质及钻孔资料,采用2.5D人机交互反演对磁测剖面上的磁铁矿体进行拟合,利用Golden Software公司开发的Voxler软件,在虚拟三维环境下实现二维小波多尺度分解数据的可视化,建立三维地质体模型,直观的预测磁铁矿体的空间范围和分布形态,实现地质、物探和地上、地下信息一体化集成展示,进行专业分析评价和辅助决策,可以有效的提高地质找矿效果。  相似文献   

CINRAD-SA双偏振雷达资料在降水估测中的应用初探   总被引：2，自引：0，他引：2  

陈超  胡志群  胡胜  张扬  李珊珊 《气象》2019,45(1):113-125

对基于水平反射率ZH和差分传播相移率K_(DP)的降水估测综合法R(C)进行了改进,并对广州S波段双偏振雷达2016年2次飑线和2次台风降水过程的Φ_(DP)使用小波分析进行滤波处理,在此基础上使用变距最小二乘法拟合得到K_(DP)的值。分别使用R(C)和R(Z_H)法对2次飑线和2次台风降水过程进行降水估算,将估算结果和雨量计小时雨量进行了对比,并将两种方法的评估结果进行了对比。结果表明:(1)对于飑线类型降水,R(C)法对5 mm·h~(-1)以上的降水估测精度要好于R(Z_H)法,且降水率越大,R(C)法优势越明显,当降水率≥20 mm·h~(-1)时,两次过程R(C)法比R(Z_H)法的平均相对误差(RE)降低了17. 2%,平均绝对误差(AE)减少了1.89 mm,平均均方根误差(RMSE)减少了1.66 mm;(2)对于台风类型降水,R(C)法对5 mm·h~(-1)以上的降水估测精度也好于R(Z_H)法,当降水率≥20 mm·h~(-1)时,两次过程R(C)法比R(Z_H)法的平均RE降低了33. 19%,平均AE减少了3. 95 mm,平均RMSE减少了4.05 mm;(3)对于飑线和台风两种类型降水R(C)法都明显改善了降水率较大时的R(Z_H)法低估问题,但R(C)法在降水率10 mm·h~(-1)时也存在低估,可能是由雨滴谱资料观测误差导致拟合的系数偏小或雷达硬件造成的观测偏差等造成的。  相似文献   

基于小波长短期记忆网络的风电功率超短期概率预测     

王朋  孙永辉  翟苏巍  候栋宸  王森 《南京气象学院学报》2019,11(4):460-466

随着大规模的风电并网,风电所具有的间歇性与随机性对电力系统的稳定性产生了很大的影响,风电功率预测成为当前解决该问题重要的方式之一.本文利用长短期记忆（LSTM）网络良好的时序记忆特性,将小波分解技术与LSTM深度网络结合,提出基于小波长短期记忆网络的风电功率超短期概率预测模型.首先通过小波分解技术将原始时间序列进行平稳化处理,再建立各子序列样本的LSTM网络预测模型,借助最大似然估计法估计预测误差的高斯分布函数,最终实现对未来4 h时刻的风电功率概率区间预测.最后,采用中国东北某风电场数据对所提方法进行算例分析,结果表明,将小波分解与深度学习方法结合可以较好地提高预测的精度,提高概率预测的区间可靠性.  相似文献   

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

Y. Chebud  A. Melesse 《水文研究》2013,27(10):1475-1483

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.  相似文献   

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

Seyed Ahmad Mirbagheri  Taher Rajaee  Amir Alikhani 《水文科学杂志》2013,58(7):1175-1189

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.  相似文献   

Discrete wavelet‐based trend identification in hydrologic time series     

Yan‐Fang Sang  Zhonggen Wang  Changming Liu 《水文研究》2013,27(14):2021-2031

Trend identification is a substantial issue in hydrologic series analysis, but it is also a difficult task in practice due to the confusing concept of trend and disadvantages of methods. In this article, an improved definition of trend was given as follows: ‘a trend is the deterministic component in the analysed data and corresponds to the biggest temporal scale on the condition of giving the concerned temporal scale’. It emphasizes the intrinsic and deterministic properties of trend, can clearly distinguish trend from periodicities and points out the prerequisite of the concerned temporal scale only by giving which the trend has its specific meaning. Correspondingly, the discrete wavelet‐based method for trend identification was improved. Differing from those methods used presently, the improved method is to identify trend by comparing the energy difference between hydrologic data and noise, and it can simultaneously separate periodicities and noise. Furthermore, the improved method can quantitatively estimate the statistical significance of the identified trend by using proper confidence interval. Analyses of both synthetic and observed series indicated the identical power of the improved method as the Mann–Kendall test in assessing the statistical significance of the trend in hydrologic data, and by using the former, the identified trend can adaptively reflect the nonlinear and nonstationary variability of hydrologic data. Besides, the results also showed the influences of three key factors (wavelet choice, decomposition level choice and noise content) on discrete wavelet‐based trend identification; hence, they should be carefully considered in practice. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

EVALUATION OF DAILY PRECIPITATION IN CHINA FROM ECMWF AND NCEP REANALYSES   总被引：2，自引：0，他引：2  

崔茂常  冯明  练树民 《中国海洋湖沼学报》2000,18(1):35-41

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Detection of anomalous seismic phases by the wavelet transform   总被引：1，自引：0，他引：1  

Kiyoshi Yomogida 《Geophysical Journal International》1994,116(1):119-130

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