共查询到19条相似文献,搜索用时 109 毫秒
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基于遗传算法的暴雨强度公式参数的优化 总被引:17,自引:2,他引:15
遗传算法是模型参数优化的一种有效方法。将遗传算法应用于北京市郊区不同重现期的暴雨强度与降雨历时关系式中参数的优化,并与传统回归法和优选回归法的优化效果进行了分析比较。实例计算结果表明:遗传算法用于暴雨强度公式中的参数估计精度高于传统回归法和优选回归法的参数估计精度。该方法具有直观、简便和实用特点。 相似文献
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将三参数Weibull分布函数表达式作为一种非线性回归模型,利用最小二乘法(LS)估计的基本思想,推导出模型参数计算的高斯-牛顿迭代公式,并用实例验证参数估计的可行性。 相似文献
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三参数Weibull分布参数估计的一种新方法 总被引:11,自引:0,他引:11
本文借助变量变换,提出一种确定三参数Weibull分布参数估计值的新方法。资料计算表贝,它不仅计算简便,而且可给出有效性高的参数估计。 相似文献
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靳小兵 《成都气象学院学报》1996,11(43):316-319
根据三轴风速仪实测大气扩散参数的实测值及其表达形式,以适当的数学方式拟合成可供大气污染物浓度预测的实用公式,并提出了三轴扩散参数实用形式的应用范围,使三轴风速仪测得的参数可直接应用于环评工作中。 相似文献
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用最小绝对偏差方法(LAD)估计极值分布参数的探讨 总被引:2,自引:3,他引:2
数理统计问题中的最小绝对偏差方法(Least Absolute Deviation)由于具有良好的稳健性,近年来备受重视。本文所研究的是如何将最小绝对偏差法及非线性回归模型相结合,应用于极值分布的参数估计,并与经典的参数估计法相比较。通过对徐州市降雨量数据的研究表明,改进后的参数估计法不仅提高了模型拟和的精确度,而且有良好的稳定性,可以推广到相关气象要素的预测、预报研究中。其中,将LAD法运用于极值分布模型是一个新的尝试。 相似文献
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自动气象站湿球温度快速计算方法 总被引:1,自引:0,他引:1
湿球温度是采暖通风、电厂冷却塔等工程设计中的重要气象参数。随着自动气象站在台站的广泛使用,湿球温度的直接观测资料逐渐停止,这给工程设计中湿球温度的气象参数分析和气象资料的应用造成了困难。对于自动气象站湿球温度的计算,现提出基于地面气象观测的湿度参量公式和牛顿迭代法基本思想,采用简化一般的迭代公式,并利用湿球温度的经验公式计算初始值,采用EXECL电子表格完成湿球温度的迭代计算。结果表明,该方法计算湿球温度,精度较高,计算量较小,计算过程简单可控,可广泛应用于自动气象站的湿球温度计算。 相似文献
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基于重庆34个国家气象站1981—2016年5 min,24 h至3 d的过程最大雨量共18个年极值降水序列,利用线性矩法计算6种常用概率分布函数的模型参数,通过备选最优模型筛选法客观选取各站各历时极值降水的最优概率模型,并将优选结果应用于重庆不同历时百年重现期降水的计算。结果表明:模型优选方法得到的重庆各站不同历时极值降水的最优线型略有差异,广义极值分布占比最大,三参数Weibull分布次之,三参数对数正态分布第三,皮尔逊Ⅲ型和Gumbel分布相当,指数分布最差。最优线型计算的重庆不同历时百年重现期降水的空间分布大值区由短历时的点状分布向长历时的片状分布转变,渝东北的大值中心受地形影响不断向北移动。基于线性矩法的概率模型参数估计及客观的线型优选过程具有较强的可操作性和适应性,可应用于其他工程气象参数的推算中。 相似文献
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Melt ponds significantly affect Arctic sea ice thermodynamic processes. The melt pond parameterization scheme in the Los Alamos sea ice model(CICE6.0) can predict the volume, area fraction(the ratio between melt pond area to sea ice area in a model grid), and depth of melt ponds. However, this scheme has some uncertain parameters that affect melt pond simulations. These parameters could be determined through a conventional parameter estimation method, which requires a large number of sensitivity simulations. The adjoint model can calculate the parameter sensitivity efficiently. In the present research, an adjoint model was developed for the CESM(Community Earth System Model) melt pond scheme. A melt pond parameter estimation algorithm was then developed based on the CICE6.0 sea ice model, melt pond adjoint model,and L-BFGS(Limited-memory Broyden-Fletcher-Goldfard-Shanno) minimization algorithm. The parameter estimation algorithm was verified under idealized conditions. By using MODIS(Moderate Resolution Imaging Spectroradiometer)melt pond fraction observation as a constraint and the developed parameter estimation algorithm, the melt pond aspect ratio parameter in CESM scheme, which is defined as the ratio between pond depth and pond area fraction, was estimated every eight days during summertime for two different regions in the Arctic. One region was covered by multi-year ice(MYI) and the other by first-year ice(FYI). The estimated parameter was then used in simulations and the results show that:(1) the estimated parameter varies over time and is quite different for MYI and FYI;(2) the estimated parameter improved the simulation of the melt pond fraction. 相似文献
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CoLM 模拟土壤温度和湿度最敏感参数的研究 总被引:2,自引:2,他引:0
合理的参数估计是提高陆面模式模拟能力的关键,而其过高的维数极大地增加了合理估计的难度。参数的敏感性分析,旨在针对目标变量找出最敏感的参数,从而实现在有限计算机资源条件下,对参数进行合理估计。本文以Common Land Model(CoLM)为研究对象,利用Morris 方法定性地从40 个参数中筛选出影响土壤温度和土壤湿度的敏感参数,并通过Sobol' 方法从敏感性顺序和各敏感参数的累积贡献率两个方面,对Morris 方法分析结果进行验证。在此基础上,本研究还利用Sobol' 方法对已筛选的参数做定量敏感性分析,最终确定参数的主效应、交互效应和总效应。研究结果表明,Morris 方法可以基于少量样本实现复杂的陆面模式的参数筛选,而Sobol' 方法的结果又从定量的角度描述了每个敏感参数对模型响应的影响程度,并且两种方法结论一致。 相似文献
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That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology.Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system,the response time scales of a model to parameters can be different,from hourly to decadal.Unlike state estimation,where the update frequency is usually linked with observational frequency,the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated.Here,with a simple coupled model,the impact of model sensitivity response time scales on coupled model parameter estimation is studied.The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere.Results show that,using the update frequency determined by the model sensitivity response time scale,both the reliability and quality of parameter estimation can be improved significantly,and thus the estimated parameters make the model more consistent with the observation.These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization. 相似文献
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Xinrong Wu Shaoqing Zhang Zhengyu Liu Anthony Rosati Thomas L. Delworth 《Climate Dynamics》2013,40(7-8):1789-1798
Observational information has a strong geographic dependence that may directly influence the quality of parameter estimation in a coupled climate system. Using an intermediate atmosphere-ocean-land coupled model, the impact of geographic dependent observing system on parameter estimation is explored within a “twin” experiment framework. The “observations” produced by a “truth” model are assimilated into an assimilation model in which the most sensitive model parameter has a different geographic structure from the “truth”, for retrieving the “truth” geographic structure of the parameter. To examine the influence of data-sparse areas on parameter estimation, the twin experiment is also performed with an observing system in which the observations in some area are removed. Results show that traditional single-valued parameter estimation (SPE) attains a global mean of the “truth”, while geographic dependent parameter optimization (GPO) can retrieve the “truth” structure of the parameter and therefore significantly improves estimated states and model predictability. This is especially true when an observing system with data-void areas is applied, where the error of state estimate is reduced by 31 % and the corresponding forecast skill is doubled by GPO compared with SPE. 相似文献
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以优势高和地位指数的估测误差最小为目标函数,采用粒子群优化算法求解地位指数曲线模型的参数.结合实例与免疫算法比较,结果表明:粒子群优化算法求解的参数使模型的总体误差更小,精度更高,拟合效果更理想,更加科学合理,同时也提高了幼林的估算精度.研究的结果为森林经营中生长模型参数的求解以及相关研究提供了新的应用思路,也拓宽了粒子群优化算法在林业科学中的应用. 相似文献
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In this paper a nonlinear method of time series analysis-threshold autoregressive (TAR) model in discrete time is used. The TAR procedure consists of four parts: model building, statistical identification, parameter estimation and forecasting.The object of this study is to estimate monthly total precipitation of Shanghai and Beijing by using open loop TAR model. We can see that the trend of forecasting is in agreement with observations. 相似文献
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因为状态空间模型既包含了未知状态,又包含了未知参数,且二者是非线性乘积关系,使得辨识问题变得复杂.针对这一问题,详细研究了规范状态空间系统的状态与参数联合估计方法.采用交互估计理论,即采用递推方法或迭代方法实现系统状态与参数的交互估计.基本思路是在计算参数估计时,辨识算法信息向量中的未知状态用其估计值代替,然后利用获得的参数估计,设计基于参数估计的状态观测器或基于参数估计的Kalman滤波算法估计系统的状态,二者形成一个交互计算过程(递阶计算过程).沿着这条思路,分别从递推方案和迭代方案,研究和提出了基于状态观测器和基于Kalman滤波状态估计的随机梯度辨识算法、递推最小二乘辨识算法、多新息随机梯度辨识算法、多新息最小二乘辨识算法,以及模型分解的辨识算法,并给出了几个典型算法的计算步骤、流程图和计算量. 相似文献