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排序方式: 共有141条查询结果,搜索用时 31 毫秒
1.
类型丰富、时空分辨率高的海洋探测数据,为信号分解和机器学习算法的应用提供了可能。本文针对如何建立有效的海温预测模型这一问题,使用高时空分辨率的海表温度(SST)融合产品,引入信号处理领域的集合经验模态分解(EEMD)和机器学习领域的自回归积分滑动平均模型(ARIMA)。首先利用最适于分解自然信号的EEMD方法,将海温数据分解成多个确定频率的序列;再利用ARIMA分别对各个频率的序列进行预测,最后将各个序列的预测结果进行组合。该方法在丰富数据的支撑下,比以往直接使用海温数据所建立的预测模型精度更高,为更好地进行海温预测提供了新方法。  相似文献   
2.
基准站受构造运动与非线性因素的影响,如何构建高精度、现势性强的精细区域框架是位置服务与形变分析的的关键.笔者提出顾及基准站坐标动态特性与稳定性的区域框架构建方法.以我国西部与东部某城市的多年连续运行基准站数据为例进行试算比对,试验结果表明:该方法是可行的,较好地顾及了基准站的坐标特性与非线性影响,考虑了基准站的垂直运动规律,可构建高精度的区域基准,可发现区域基准的微动态变化.  相似文献   
3.
基于黄河源区8个站点的年平均气温序列,利用集合经验模态分解(Ensemble Empirical Mode Decomposition,EEMD)方法,揭示了以玛多站为代表的黄河源区1953~2017年气温演变的多时间尺度特征,探讨不同时间尺度上的周期振荡对气温变化总体特征的影响程度,分析了黄河源区不同时间尺度的气温变化与海温指数,尤其是与北大西洋多年代际振荡(Atlantic Multidecadal Oscillation,AMO)间的关系。结果表明:(1)1953年以来黄河源区玛多站年平均气温以0.31 ℃/10 a的变化率表现为明显的增暖趋势,20世纪80年代后期开始转暖,尤其是进入20世纪90年代后期变暖更加明显。(2)1953~2017年,黄河源区年平均气温呈现3 a、6 a、11 a、25 a、64 a及65 a以上时间尺度的准周期变化,其中以准3 a和65 a以上时间尺度的振荡最显著,准3 a的年际振荡在21世纪以前振幅较大,而进入21世纪后年际振荡振幅减弱,65 a以上时间尺度的年代际振荡振幅明显加大。(3)1998年气候显著变暖以前,以准3 a周期为代表的年际振荡在气温演变过程中占据主导地位,1998年气候显著变暖以后,65 a以上时间尺度周期振荡的贡献率增加近5倍,与准3 a周期振荡的贡献相当。(4)气温与Nino3.4指数和PDO(Pacific Decadal Oscillation)指数的同期相关均不显著,但当气温领先PDO指数22 a时正相关最大且显著,不同于PDO指数,气温原始序列及其3个年代际尺度分量滞后AMO指数3~7 a或二者同期时相关性最高,这就意味着AMO对黄河源区气温具有显著影响。(5)AMO的正暖位相对应着包括中国的整个东亚地区偏暖,黄河源区只是受影响区域的一部分,20世纪60年代至90年代初期AMO的负冷位相期、20世纪90年代中后期至今AMO的正暖位相与黄河源区气温距平序列的负距平、正距平相对应,气温在65 a以上时间尺度的变化与AMO指数相关性更高,可见,AMO是影响黄河源区气温变化的一个重要的气候振荡,这种影响主要表现在年代际时间尺度上。  相似文献   
4.
《Polar Science》2014,8(2):207-216
Fungal colonization, succession, and decomposition of leaves and stems of Salix arctica were studied to estimate the roles of fungi in the decomposition processes in the high Arctic. The samples were collected from five moraines with different periods of development since deglaciation to investigate the effects of ecosystem development on the decomposition processes during the primary succession. The total hyphal lengths and the length of darkly pigmented hyphae increased during decomposition of leaves and stems and were not varied with the moraines. Four fungal morphotaxa were frequently isolated from both leaves and stems. The frequencies of occurrence of two morphotaxa varied with the decay class of leaves and/or stems. The hyphal lengths and the frequencies of occurrence of fungal morphotaxa were positively or negatively correlated with the contents of organic chemical components and nutrients in leaves and stems, suggesting the roles of fungi in chemical changes in the field. Pure culture decomposition tests demonstrated that the fungal morphotaxa were cellulose decomposers. Our results suggest that fungi took part in the chemical changes in decomposing leaves and stems even under the harsh environment of the high Arctic.  相似文献   
5.
We develop a new Proper Orthogonal Decomposition (POD) reduced order model for saturated groundwater flow, and apply that model to an inverse problem for the hydraulic conductivity field. We use sensitivities as the POD basis. We compare the output when the optimizer uses the reduced order model against results obtained with a full PDE based model. The solutions generated using the POD reduced model are comparable in residual norm to the solutions formed using only the full-scale model. The material parameters are similarly comparable. The time to solution when using the reduced model is reduced by at least an order of magnitude, as are the number of calls to the full model.  相似文献   
6.
河口水下三角洲是河流和海洋环境共同作用的产物,沉积地层中蕴藏了许多环境变化信息.在长江口水下三角洲泥质区采集了柱样SC09,首先利用放射性同位素210Pb确定了沉积柱样的平均沉积速率,其次对沉积柱样以0.2 cm间隔进行高分辨率取样,获得了沉积物粒度参数,然后提取了沉积物粒度敏感组分,并对其进行了经验模态分解(EMD)...  相似文献   
7.
In this paper, a new snow wetness estimation model is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. Surface and volume are the dominant scattering components in wet-snow conditions. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized surface and volume parameters are utilized to invert snow surface and volume dielectric constants using the Bragg coefficients and Fresnel transmission coefficients respectively. The snow surface and volume wetness are then estimated using an empirical relationship. The effective snow wetness is derived from the weighted averaged surface and volume snow wetness. The weights are derived from the normalized surface and volume scattering powers obtained from the generalized full-polarimetric SAR decomposition method. Six Radarsat-2 fine resolution full-polarimetric datasets acquired over Himachal Pradesh, India along with the near-real time in situ measurements were used to validate the proposed model. The snow wetness derived from the SAR data by the proposed model with in situ measurements indicated that the absolute error at 95% confidence interval is 1.3% by volume.  相似文献   
8.
A voice enhancement algorithm based on the Empirical Mode Decomposition (EMD) and the improved spectral subtraction is proposed for the low-SNR (Signal Noise Ratio) shortwave time signal. This method is proposed to solve the problem that the shortwave time signal cannot be used for timing in complex noisy environments. The core idea of this method is to use the Hilbert-Huang Transform (HHT) algorithm to make the empirical mode decomposition on the noisy shortwave signal, and to select the intrinsic mode functions containing the shortwave signal information for the signal reconstruction by through the maximum correlation. Then, to make the spectral subtraction on the reconstructed signal to achieve the purpose of noise reduction. The experimental result shows that this method has a better noise reduction than the traditional methods.  相似文献   
9.
In this paper, a new snow density estimation methodology is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized volume parameter is utilized to invert snowpack dielectric constant using the Fresnel transmission coefficients. The snow density is then estimated using an empirical relationship. Six Radarsat-2 fine resolution full-polarimetric C-band datasets were acquired over Himachal Pradesh, India. The near-real time in-situ measurements were collected with the satellite pass to validate the proposed method. The mean absolute error (MAE) of the proposed method is 0.027 g cm−3 and the root mean square error (RMSE) is 0.032 g cm−3. The snow density variation within a season were also analyzed using multi-temporal Radarsat-2 data.  相似文献   
10.
高分辨率的树木年轮是记录历史时期气候变化的良好生物载体,在古气候研究中被广泛应用。但年轮宽度与气候因子之间有着复杂的联系,这种关系受气候因子之间的相互制衡和因物种而异的树木生长节律的共同影响。在利用树木年轮开展历史时期气候变化的研究中,剔除树木年轮与年龄相关的生长趋势是准确获取气候信号的先决条件。然而,传统的和相对改进的一些树轮标准化方法在拟合并剔除树龄相关的趋势及非气候干扰信息方面仍存在一些问题。本文利用经验模态分解(EMD)方法进行树轮资料的标准化方法研究, 对已获得的树轮生长序列所记录的信息进行分解,得到一系列不同物理意义的本征模态分量,结合多样本信息的对比及生物学特性,深入解读各分量表征的气候变化、环境干扰及缓慢生长趋势项等不同物理意义,进而剔除非气候信息,得到可以准确反映气候变化的代用序列,并将该方法与目前广泛采用的标准化方法进行对比,分析不同方法的利弊所在,为进一步改进树轮标准化方法提供新思路。  相似文献   
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