共查询到20条相似文献，搜索用时 31 毫秒
1.
Abstract A procedure is presented for using the bivariate normal distribution to describe the joint distribution of storm peaks (maximum rainfall intensities) and amounts which are mutually correlated. The Box-Cox transformation method is used to normalize original marginal distributions of storm peaks and amounts regardless of the original forms of these distributions. The transformation parameter is estimated using the maximum likelihood method. The joint cumulative distribution function, the conditional cumulative distribution function, and the associated return periods can be readily obtained based on the bivariate normal distribution. The method is tested and validated using two rainfall data sets from two meteorological stations that are located in different climatic regions of Japan. The theoretical distributions show a good fit to observed ones. 相似文献
2.
Hilbert-Huang变换在提取地震信号动力特性中的应用 总被引：1，自引：0，他引：1
H ilbert-Huang变换(HHT)是一种处理非线性、非平稳信号的新方法。它通过经验模态分解将信号分解为有限个固有模态函数,并对每个固有模态函数进行H ilbert变换得到H ilbert谱。本文将这种方法应用于地震信号动力特性的提取,有效地获得了信号能量的时频分布,量化提取了中心频率、瞬时相位、瞬时能量、H ilbert能量、最大振幅对应的时频分布等动力特性,并与Fourier变换、小波变换等进行了比较,显示了HHT的优势以及对于进一步实现结构分析和控制的重要意义。 相似文献
3.
L. Valadares Tavares R. C. Souza 《Stochastic Environmental Research and Risk Assessment (SERRA)》1988,2(4):295-302
Nonlinear serial dependence and skewness of annual hydrologic time series {X
t
} have been challenging the classical theory of Gaussian stochastic processes, particularly if the study of extremes (dry or wet years) is required as it is often the case. In this paper, a new and general model is proposed assuming that the geophysical system which is responsible forX
t
can take different states and that this state process is modeled by a Markov chain. At each time,X
t
is generated from a statistical distribution which depends on the state that has occurred. This model can preserve non-linear structures of serial dependence and it can produce a skewed marginal distribution ofX
t
without any transformation. A successful application of this model to the study of annual rainfall at Fortaleza (Northeast of Brazil) is also presented. 相似文献
4.
阵列声波信号是典型的非线性、非平稳信号,其动力特性的量化提取对于进行地层结构构造分析提供了必要的基础资料.而Hilbert-Huang变换(HHT)是一种处理非线性、非平稳信号的新方法.它通过经验模态分解(EMD)将信号分解为有限个固有模态函数(IMF),并对每个固有模态函数进行Hilbert变换得到Hilbert谱.本文将这种方法应用于阵列声波信号动力特性的提取,有效地获得了信号能量的时频分布,瞬时能量、Hilbert能量、最大振幅对应的时频分布等动力特性,显示了HHT的优势以及对于进一步实现地层结构构造分析的重要意义. 相似文献
5.
Kasemsan Manomaiphiboon Sun-Kyoung Park Armistead G. Russell 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(2):159-168
Probabilistic characterization of environmental variables or data typically involves distributional fitting. Correlations,
when present in variables or data, can considerably complicate the fitting process. In this work, effects of high-order correlations
on distributional fitting were examined, and how they are technically accounted for was described using two multi-dimensional
formulation methods: maximum entropy (ME) and Koehler–Symanowski (KS). The ME method formulates a least-biased distribution
by maximizing its entropy, and the KS method uses a formulation that conserves specified marginal distributions. Two bivariate
environmental data sets, ambient particulate matter and water quality, were chosen for illustration and discussion. Three
metrics (log-likelihood function, root-mean-square error, and bivariate Kolmogorov–Smirnov statistic) were used to evaluate
distributional fit. Bootstrap confidence intervals were also employed to help inspect the degree of agreement between distributional
and sample moments. It is shown that both methods are capable of fitting the data well and have the potential for practical
use. The KS distributions were found to be of good quality, and using the maximum likelihood method for the parameter estimation
of a KS distribution is computationally efficient. 相似文献
6.
Bivariate frequency analysis of nonstationary low‐flow series based on the time‐varying copula 
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下载免费PDF全文 Many studies have analysed the nonstationarity in single hydrological variables due to changing environments. Yet, few researches have been done to investigate how the dependence structure between different individual hydrological variables is affected by changing environments. To investigate how the reservoirs have altered the dependence structure between river flows at different locations on the Hanjiang River, a time‐varying copula model, which takes the nonstationarity in the marginal distribution and/or the time variation in dependence structure between different hydrological series into consideration, is presented in this paper to perform a bivariate frequency analysis for the low‐flow series from two neighbouring hydrological gauges. The time‐varying moments model with either time or reservoir index as explanatory variables is applied to build the time‐varying marginal distributions of the two low‐flow series. It's found that both marginal distributions are nonstationary, and the reservoir index yields better performance than the time index in describing the nonstationarities in the marginal distributions. Then, the copula with the dependence parameter expressed as a function of either time or reservoir index is applied to model the variable dependence between the two low‐flow series. The copula with reservoir index as the explanatory variable of the dependence parameter has a better fitting performance than the copula with the constant or the time‐trend dependence parameter. Finally, the effect of the time variation in the joint distribution on three different types of joint return periods (i.e. AND, OR and Kendall) of low flows at two neighbouring hydrological gauges is presented. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
7.
A nonparametric method for resampling multiseason hydrologic time series is presented. It is based on the idea of rank matching, for simulating univariate time series with strong and/or long‐range dependence. The rank matching rule suggests concatenating with higher likelihood those blocks that match at their ends. In the proposed method, termed ‘multiseason matched block bootstrap’, nonoverlapping within‐year blocks of hydrologic data (formed from the observed time series) are conditionally resampled using the rank matching rule. The effectiveness of the method in recovering various statistical attributes, including the dependence structure from finite samples generated from a known population, is demonstrated through a two‐level hypothetical Monte Carlo simulation experiment. The method offers enough flexibility to the modeller and is shown to be appropriate for modelling hydrologic data that display strong dependence, nonlinearity and/or multimodality in the time series depicting the hydrologic process. The method is shown to be more efficient than the nonparametric ‘k‐nearest neighbor bootstrap’ method in simulating the monthly streamflows that exhibit a complex dependence structure and bimodal marginal probability density. Even with short block sizes, this bootstrap method is able to predict the drought characteristics reasonably accurately. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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Stochastic rainfall models are widely used in hydrological studies because they provide a framework not only for deriving information about the characteristics of rainfall but also for generating precipitation inputs to simulation models whenever data are not available. A stochastic point process model based on a class of doubly stochastic Poisson processes is proposed to analyse fine-scale point rainfall time series. In this model, rain cells arrive according to a doubly stochastic Poisson process whose arrival rate is determined by a finite-state Markov chain. Each rain cell has a random lifetime. During the lifetime of each rain cell, instantaneous random depths of rainfall bursts (pulses) occur according to a Poisson process. The covariance structure of the point process of pulse occurrences is studied. Moment properties of the time series of accumulated rainfall in discrete time intervals are derived to model 5-min rainfall data, over a period of 69 years, from Germany. Second-moment as well as third-moment properties of the rainfall are considered. The results show that the proposed model is capable of reproducing rainfall properties well at various sub-hourly resolutions. Incorporation of third-order moment properties in estimation showed a clear improvement in fitting. A good fit to the extremes is found at larger resolutions, both at 12-h and 24-h levels, despite underestimation at 5-min aggregation. The proportion of dry intervals is studied by comparing the proportion of time intervals, from the observed and simulated data, with rainfall depth below small thresholds. A good agreement was found at 5-min aggregation and for larger aggregation levels a closer fit was obtained when the threshold was increased. A simulation study is presented to assess the performance of the estimation method. 相似文献
10.
双线性单自由度体系强迫动力反应的Hilbert谱与本征振动模态:输入简谐波频率的影响 总被引：5，自引：1，他引：4
系统地研究了双线性单自由度体系在简谐波输入下表现出非线性力学行为时,输入简谐波频率对体系动力响应的Hilbert谱、Hilbert边缘谱及Fourier幅值谱的影响.研究结果表明,如果体系输入简谐波频率为f,那么体系动力响应Hilbert边缘谱的能量分布在f附近一个较宽的频带上,该频带的产生是体系动力响应Hilbert谱中所蕴含的波内调制的必然结果,它源自于体系某个本征振动模态瞬时频率的波动,而这种瞬时频率的波动描述了体系屈服与卸载的非线性力学行为;体系动力响应的Fourier幅值谱自3f起,每隔2f就会出现一个幅值明显高出周围其它分量的Fourier“伪”谐波分量,这也是体系非线性力学行为所造成的结果. 相似文献
11.
The knowledge of the high intensity tails of probability distributions that determine the rate of occurrence of extreme events of solar energetic particles is a critical element in the evaluation of hazards for human and robotic space missions. Here instead of the standard approach based on fitting a selected distribution function to the observed data we investigate a different approach, which is based on a study of the scaling properties of the maximum particle flux in time intervals of increasing length. To find the tail of the probability distributions we apply the “Max-Spectrum” method (Stoev, S.A., Michailidis, G., 2006. On the estimation of the heavy-tail exponent in time series using the Max-Spectrum. Technical Report 447, Department of Statistics, University of Michigan) to 1973–1997 IMP-8 proton data and the 1987–2008 GOES data, which cover a wide range of proton energies. We find that both data sets indicate a power-law tail with the power exponents close to 0.6 at least in the energy range 9–60 MeV. The underlying probability distribution is consistent with the Fréchet type (power-law behavior) extreme value distribution. Since the production of high fluxes of energetic particles is caused by fast Coronal Mass Ejections (CMEs) this heavy-tailed distribution also means that the Sun generates more fast CMEs than would be expected from a Poissonian-type process. 相似文献
12.
S. Salcedo-Sanz J.L. Camacho .M. Prez-Bellido E. Hernndez-Martín 《Journal of Atmospheric and Solar》2010,72(18):1333-1340
In this paper we present a novel method for deseasonalizing TOC data using non-linear models, with evolutionary computation techniques, and its performance with a neural network as regression approach. Specifically, the proposed deseasonalization method uses an evolutionary programming (EP) approach to carry out a curve fitting problem, where a given function model is optimized to be as similar as possible to an objective curve (a real TOC measurement in this case). Different non-linear models are proposed to be optimized with the EP algorithm. In addition, we test the possibility of deseasonalizing the TOC measurement and also the meteorological input data. The deseasonalized series is then used to train a neural network (multi-layer perceptron). We test the proposed models in the prediction of several TOC series in the Iberian Peninsula, where we carry out a comparison against a reference deseasonalizing model previously proposed in the literature. The results obtained show the good performance of some of the deseasonalizing models proposed in this paper. 相似文献
13.
Estimating Aquifer Properties Using Derivative Analysis of Water Level Time Series from Active Well Fields 下载免费PDF全文
下载免费PDF全文 Water level time series from groundwater production wells offer a transient dataset that can be used to estimate aquifer properties in areas with active groundwater development. This article describes a new parameter estimation method to infer aquifer properties from such datasets. Specifically, the method analyzes long‐term water level measurements from multiple, interacting groundwater production wells and relies on temporal water level derivatives to estimate the aquifer transmissivity and storativity. Analytically modeled derivatives are compared to derivatives calculated directly from the observed water level data; an optimization technique is used to identify best‐fitting transmissivity and storativity values that minimize the difference between modeled and observed derivatives. We demonstrate how the consideration of derivative (slope) behavior eliminates uncertainty associated with static water levels and well‐loss coefficients, enabling effective use of water level data from groundwater production wells. The method is applied to time‐series data collected over a period of 6 years from a municipal well field operating in the Denver Basin, Colorado (USA). The estimated aquifer properties are shown to be consistent with previously published values. The parameter estimation method is further tested using synthetic water level time series generated with a numerical model that incorporates the style of heterogeneity that occurs in the Denver Basin sandstone aquifers. 相似文献
14.
In this paper, an effective active predictive control algorithm is developed for the vibration control of non-linear hysteretic structural systems subjected to earthquake excitation. The non-linear characteristics of the structural behaviour and the effects of time delay in both the measurements and control action are included throughout the entire analysis (design and validation). This is very important since, in current design practice, structures are assumed to behave non-linearly, and time delays induced by sensors and actuator devices are not avoidable. The proposed algorithm focuses on the instantaneous optimal control approach for the development of a control methodology where the non-linearities are brought into the analysis through a non-linear state vector and a non-linear open-loop term. An autoregressive (AR) model is used to predict the earthquake excitation to be considered in the prediction of the structural response. A performance index that is quadratic in the control force and in the predicted non-linear states, with two additional energy related terms, and that is subjected to a non-linear constraint equation, is minimized at every time step. The effectiveness of the proposed closed-open loop non-linear instantaneous optimal prediction control (CONIOPC) strategy is presented by the results of numerical simulations. Since non-linearity and time-delay effects are incorporated in the mathematical model throughout the derivation of the control methodology, good performance and stability of the controlled structural system are guaranteed. Copyright © 1999 John Wiley & Sons, Ltd. 相似文献
15.
在确定海平面上升速率时,传统方法是利用最小二乘拟合获取特定时间段内的平均速率.事实上,由于海平面是一种非稳态变化,其速率随着时间变化.本文使用集成经验模态分解获取海平面变化在2002-2014年间的非线性趋势,然后通过三次样条函数平滑拟合非线性趋势得到连续的一阶导数,即为海平面变化的瞬时速率.结果表明,全球平均海平面的瞬时速率先降后升：从2002的2.7 mm·a-1缓慢下降至2010年的2.5 mm·a-1,然后上升至2014年的3.8 mm·a-1.通过分析海平面上升各个贡献成分的瞬时速率,发现该上升主要由海水质量增加引起.在2002-2014年间,格陵兰岛冰川消融对海平面上升瞬时速率的贡献从0.51 mm·a-1上升至0.85mm·a-1,南极冰川消融的贡献则从0.12 mm·a-1上升至0.34 mm·a-1.陆地水储量对海平面上升起抑制作用,但该抑制作用呈下降趋势,其瞬时速率从-0.24 mm·a-1增加到0.03 mm·a-1.比容海平面的瞬时速率表现为下降趋势,从1.6 mm·a-1减小至1.0 mm·a-1.这表明在全球尺度上,海水质量对海平面上升的贡献正在增加,截止到2014年,海水质量的贡献已经接近70%. 相似文献
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Wigner-Ville分布及其在地震衰减估计中的应用 总被引：1，自引：1，他引：1
地震信号的衰减一般是在频域内利用信号功率谱的统计性质进行表征。但是,传统的基于傅立叶变换的功率谱估计方法的分辨率较低,使得衰减估计的精度较低。Wigner-Ville分布是一种重要的Cohen类时频分布,它具有一系列的优良性质,如时频边缘分布性质、好的时频聚集性等。这些性质对信号的时频分析具有重要意义。因此,Wigner-Ville分布为地震信号的衰减估计提供了新的手段。本文首先介绍了Wigner-Ville分布以及能够减少或消除交叉项影响的平滑Wigner-Ville分布,然后,提出了一种基于Wigner-Ville分布的衰减估计方法。在这一方法中,利用Wigner-Ville分布得到的瞬时能量谱中高频段的能量下降速率度量衰减。将这一方法应用到塔中地区奥陶系礁滩相碳酸盐岩储层预测,结果表明,基于Wigner-Ville分布的衰减能够有效地检测出礁滩相带和泻湖区域之间衰减特性的差异。 相似文献
18.
Applicability of Wakeby distribution in flood frequency analysis: a case study for eastern Australia 总被引：1，自引：0，他引：1 下载免费PDF全文
下载免费PDF全文 Ataur Rahman Mohammad A. Zaman Khaled Haddad Salaheddine El Adlouni Chi Zhang 《水文研究》2015,29(4):602-614
Parametric method of flood frequency analysis (FFA) involves fitting of a probability distribution to the observed flood data at the site of interest. When record length at a given site is relatively longer and flood data exhibits skewness, a distribution having more than three parameters is often used in FFA such as log‐Pearson type 3 distribution. This paper examines the suitability of a five‐parameter Wakeby distribution for the annual maximum flood data in eastern Australia. We adopt a Monte Carlo simulation technique to select an appropriate plotting position formula and to derive a probability plot correlation coefficient (PPCC) test statistic for Wakeby distribution. The Weibull plotting position formula has been found to be the most appropriate for the Wakeby distribution. Regression equations for the PPCC tests statistics associated with the Wakeby distribution for different levels of significance have been derived. Furthermore, a power study to estimate the rejection rate associated with the derived PPCC test statistics has been undertaken. Finally, an application using annual maximum flood series data from 91 catchments in eastern Australia has been presented. Results show that the developed regression equations can be used with a high degree of confidence to test whether the Wakeby distribution fits the annual maximum flood series data at a given station. The methodology developed in this paper can be adapted to other probability distributions and to other study areas. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
19.
A method to identify the P-arrival of microseismic signals is proposed in this work, based on the algorithm of intrinsic timescale decomposition (ITD). Using the results of ITD decomposition of observed data, information of instantaneous amplitude and frequency can be determined. The improved ratio function of short-time average over long-time average and the information of instantaneous frequency are applied to the time-frequency-energy denoised signal for picking the P-arrival of the microseismic signal. We compared the proposed method with the wavelet transform method based on the denoised signal resulting from the best basis wavelet packet transform and the single-scale reconstruction of the wavelet transform. The comparison results showed that the new method is more effective and reliable for identifying P-arrivals of microseismic signals. 相似文献
20.
Abstract A trial is made to explore the applicability of chaos analysis outside the commonly reported analysis of a single chaotic time series. Two cross-correlated streamflows, the Little River and the Reed Creek, Virginia, USA, are analysed with regard to the chaotic behaviour. Segments of missing data are assumed in one of the time series and estimated using the other complete time series. Linear regression and artificial neural network models are employed. Two experiments are conducted in the analysis: (a) fitting one global model and (b) fitting multiple local models. Each local model is in the direct vicinity of the missing data. A nonlinear noise reduction method is used to reduce the noise in both time series and the two experiments are repeated. It is found that using multiple local models to estimate the missing data is superior to fitting one global model with regard to the mean squared error and the mean relative error of the estimated values. This result is attributed to the chaotic behaviour of the streamflows under consideration. 相似文献