作　　者： ; ;

机构地区： 湖南大学土木工程学院

出　　处： 《水利学报》 2006年第6期687-693,共7页

摘　　要： 本文采用Dobbins-BOD-DO水质模型,用仿真试验模拟了随机噪声干扰对河流水质模型参数估计的影响。试验表明,最小二乘(LS)估计方法关于有色噪声和较高水平白噪声干扰不具鲁棒性,噪声干扰使估计参数漂离系统真实参数。为了克服随机噪声对河流水质模型参数估计的干扰,提出了一种水质模型参数的鲁棒估计方法,即基于M-估计的信赖域算法。通过对比试验和计算表明,M-估计对于有色噪声和白噪声干扰具有鲁棒性,无论是没有扰动情况还是有各种水平各种噪声类型的干扰情况,该方法能稳健可靠地搜索到真实值,且在估值精度、收敛性、抗噪性和鲁棒性方面均优于最小二乘(LS)估计方法。 The Dobbins BOD-DO water quality model is applied to study the effect of random noise on parameter estimation by means of numerical simulation. The result shows that the least squares estimation of parameters is not robust in case of colored noises and high-level white noise involved. The random noises result in the estimated parameters drifted away from their true values. In order to overcome the disturbance of noises, a robust identification method of water quality model parameters namely trust region algorithm based on M-estimation is proposed. The calculation results indicate that the M-estimation has strong robustness and the true value of parameters can be reliably and robustly acquired either in condition of non-disturbed data or in case of noise involved. The comparison between two kinds of estimation methods shows that the trust region algorithm possesses high accuracy, excellent performance of noise resistance and strong robustness as well as uniform convergence, which are obviously better than the least squares estimation.

关 键 词： 估计 信赖域算法 水质模型 水质参数 有色噪声 白噪声

领　　域： [环境科学与工程]