三水源新安江模型的函数曲面参数率定方法

目前常规的以误差平方和为目标函数的参数估计方法存在着诸如给非线性函数增加不相关的局部优值等问题,采用函数曲面参数率定方法展开样本函数的泰勒级数,给定参数初值,通过最小二乘估计新的参数向量。以三水源新安江模型为例,将该方法应用于理想模型及邵武、东张两个实际模型的日模参数优选中。理想模型的研究结果表明,该方法随率定参数个数的增多,迭代次数有所增加;实际模型的研究结果表明,由该方法率定的参数在率定期及检验期算出的结果相对误差普遍较小。     

基于参数线性化率定法的HBV模型的优化算法及应用

针对以误差平方和最小为目标函数率定非线性函数参数会增加不相关局部优值的问题,提出了基于参数线性化率定法的HBV模型的优化算法,给出了该法的优化过程,并将其应用于大型（建溪）、中型（富水水库）、小型（对河口水库）流域中对日模拟中敏感性参数进行率定。结果表明,该方法率定效果较好,率定参数合理,与初值选取无关,率定结果基本一致,未出现不稳定现象,且循环次数少、精度高、适用范围广。     

目标函数对HEC-HMS模型参数率定的影响研究

以清江流域(渔峡口以上)为例,采用分布式水文模型HEC-HMS研究了模型参数自动率定功能,并选取参数优化的目标函数,以探讨目标函数的选取对模型模拟结果的影响,并分析其原因.结果表明,峰值加权均方根误差目标函数的模拟效果最佳,为选取其他洪水模拟参数优化目标函数提供了理论依据.     

基于SCE-UA算法的新安江日模型参数优化稳定性分析

为了探讨水文模型参数优化结果在不同流域上的稳定性,采用SCE-UA算法优化了抚河流域内的娄家村、南丰、沙子岭子流域新安江日模型参数,以径流总量误差最小和纳什效率系数最大为目标函数,分别对参数优化结果进行分析。结果表明,其中有3个新安江日模型参数(上层张力水容量W_(WUM)、下层张力水容量W_(WLM)、张力水容量W_(WDM))在三个子流域上的率定结果的稳定性相差较大,有1个参数(表层自由水容量曲线方次E_(EX))率定结果有波动,剩余的12个参数的率定结果均较稳定。通过分析新安江日模型参数的稳定性,可为未来新安江模型参数优化的理论研究提供重要参考依据。     

目标函数不确定性对汉江安康以上流域水文模拟的影响

不同优化算法和目标函数组合将导致不同的模拟结果,进而影响流域水文预报精度。通过设定不同目标函数组合方案,对比汉江上游安康以上流域在多目标优化算法(NSGA-Ⅱ和MOPSO)下对HyMod模型性能评估的影响,并识别季尺度目标函数统计规律与模拟精度的本质联系。结果表明,NSGA-Ⅱ算法更适合于汉江流域(年尺度、季尺度模拟精度更优);模拟值与实测值的拟合误差控制函数和高流量误差控制的函数(F_2、F_3)为多目标模型参数校准的首选目标函数,其重要性大于水量模拟的误差控制函数和枯水流量的误差控制函数(F_1、F_4)。     

基于傅里叶级数频率分解的汇流参数确定方法初探

采用傅里叶级数频率分解特性将总径流包含的3种不同频率水源分离,构建了不同水源间参数独立且和频率相关的目标函数,通过理想模型的实例分析验证了该方法的可行性.结果表明,该方法信息量增加,实现了汇流参数分层分频率定,解决了汇流参数率定的局部优值、率定结果不稳定和不合理问题.     

基于TOPSIS法的水文模型多目标参数自动优选方法研究

将TOPSIS法与遗传算法相结合,以径流总量误差、总径流过程均方误、洪峰过程均方误和枯水过程均方误为目标函数,采用均方差确定目标函数权重,利用四个流域连续雨洪资料对新安江模型进行多目标参数优选,并与距离函数法比较,探讨其对水文模型多目标参数优选的适应性。结果表明,TOPSIS法和距离函数法模拟效果相当,基于TOPSIS法的多目标参数优选优于单目标参数优选。     

基于种群进化的多目标参数优化

介绍一种基于种群进化TOPMODEL的多目标参数优选方法,并以该法为例,以四个描述水文过程线不同特征的函数为目标函数在酉水河流域进行研究,并取得较好的模拟结果。对优化得到的Pareto集,采用平衡聚合法求得折衷解,参数模拟的结果与观测数据有较好的吻合。用这种方法进行参数率定方便,并能保证结果的客观性和全局最优。     

基于多目标GLUE算法的新安江模型参数不确定性研究

针对新安江水文模型参数的不确定性问题,以湘江湘潭断面控制流域为例,采用新安江日模型和两个纳什效率系数作为水文模型参数率定的目标函数,结合SCE-UA优化算法,分析了不同目标函数对实测径流的模拟能力,在此基础上进一步分析了单目标GLUE方法、多目标GLUE方法和NSGA-Ⅱ优化算法获得不确定性区间特征值。结果表明,不同目标函数对径流过程显示了不同的模拟性能;NSGA-Ⅱ算法可优化多目标拥有较小的不确定性区间,但区间对实测值的覆盖率较小;与单目标算法相比,在相同的区间宽度下,多目标GLUE方法具有更高的区间覆盖率。     

基于Morris法的HBV模型参数敏感性分析

随着社会的发展和科技的进步,基于计算机运算的水文模型越来越多地应用于各个流域。为了提高水文模型的预测精度,选择误差平均值、均方根误差、相关系数、转换后的均方根误差和流量历时曲线斜率为目标函数,以绥芬河流域2009~2012年的降水径流资料为基础,通过Morris方法运行HBV模型,分析不同目标函数下参数敏感度指数的值及置信区间收敛情况,发现不同目标函数下参数的敏感性有差异,参数越敏感,达到收敛需要的样本数越多。     

水文序列的模拟生成方法

本文给出了PARMA模型的似然函数及模型参数的估计方法,引入了观测方程构成改进模型,并提出了偏态修正方法。用该模型生成了井岗山梯级水电站一级坝址处旬径流序列。     

Implementation of Geometrical Domain Decomposition Method for Solution of Axisymmetric Transient Inverse Heat Conduction Problems

The objective of this article is to study the performance of iterative parameter and function estimation techniques to solve simultaneously two unknown functions (quadratic in time, and linear in time and space) using transient inverse heat conduction method in conjunction with a geometrical domain decomposition approach, in cylindrical coordinates. For geometrical decomposition of physical domain, a multi-block method has been used. The numerical scheme for the solution of the governing partial differential equations is the finite element method. The results of the present study for a configuration composed of two joined disks with different heights are compared to those of exact heat source and temperature boundary condition using inverse analysis. Good agreement between the estimated results and exact functions has been observed for parameter estimation techniques in contrast to those of function estimation approach. In summary, the results show that the function estimation technique is sensitive to the location of measurement points, but is useful to estimate unknown functions without a priori knowledge of the functions' spatial and/or temporal distributions. However, the function estimation technique suffers from a drawback: its implementation and data extraction are less straightforward than parameter estimation method. Finally, it is shown that the use of geometrical domain decomposition offers the possibility of developing a robust inverse analysis code for general purpose heat conduction problems.     

Accurate estimation of cost function parameters for thermal power plants using a novel optimization approach

Accurate parameter estimation of the input-output characteristics in thermal power plants is an important issue in power system because these characteristics directly affect the economic dispatch calculations. Parameter estimation is an optimization problem in which the optimal values of the unknown parameters should be estimated by an optimization technique. By considering the valve-point effect, the parameter estimation will be more difficult since the fitness function of this optimization problem turns into a non-smooth and non-convex function in which finding the global optimal is a challenging task. In this paper, a recently proposed metaheuristic approach, crow search algorithm (CSA), is proposed for accurate estimation of the input-output characteristics of thermal power plants with and without valve-point effect. Simulation results show that CSA finds more promising results than least squares method (LSM), particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC).     

测风数据的时间间隔对风速概率分布参数计算的影响

风电场风速概率分布是体现风能资源统计特性的重要指标.文章在认为风速服从双参数威布尔分布的前提下,对于不同时间间隔所记录的风数据,分别应用最小二乘法、平均风速和标准差估算法、平均风速和最大风速估算法求解风速概率分布参数,由此估算出能直接体现风能资源状况的风能特征指标值.比较由风速概率分布推算出风能特征指标的估计值与由记录...     

多变量水文联合分布方法及Copula函数的应用研究

简介了水文事件中的多变量联合分布计算方法,系统总结了Copula函数的原理、性质、水文计算中常用的函数类型、参数估计方法及拟合检验方法,探讨了Copula函数在水文方面的应用前景.     

Application of Simulated Annealing for Simultaneous Estimation of Parameters in a Cylindrical Fin

An inverse problem is solved for simultaneous three parameter estimation in a large-sized cylindrical fin involving conduction-convection heat transfer. The temperature field used for the estimation of unknowns is calculated from the finite difference method (FDM). The simulated annealing (SA) is applied in this work for minimizing the required objective function. The accuracy of the estimated parameters has been studied for different measurement points, initial guess, measurement errors, and number of iterations; CPU times are also reported. The FDM-SA is observed to reconstruct the temperature field with an excellent accuracy, but ill-posed behavior is observed.     

SOC estimation of lithium battery based online parameter identification and AEKF

SOC的准确估计对提高电池的动态性能和能量利用效率至关重要,估计过程中,模型参数不准确以及系统噪声的不确定性都会对结果产生较大影响。为减小模型参数辨识和系统噪声对SOC估计精度的影响,本文采用二阶RC等效电路模型,结合自适应扩展卡尔曼滤波算法（AEKF）进行锂电池的SOC估计。用带有遗忘因子的最小二乘法对模型参数进行在线辨识,以减小由参数辨识引起的估计误差,AEKF可以对系统和过程噪声进行修正,从而减小噪声对SOC估计的影响。最后分别用EKF和AEKF进行SOC估计并比较其误差,结果表明,AEKF联合最小二乘法参数在线辨识具有更高的精度和更好的适应性。     

A new estimation approach for determining the I-V characteristics of solar cells

A new application of pattern search optimization technique for estimating the parameters of solar cell and PV module is introduced in this article. The estimated parameters are the generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor. A new objective function formulation is introduced to guide the estimation technique toward the model parameters. The proposed approach is tested and validated using different test cases, e. g. solar cell and PV module, to show its potential. Outcomes of the developed approach are compared with those of different parameter estimation techniques to measure its accuracy. Comparison results are in favor of pattern search algorithm in all cases.