基于免疫克隆选择算法的马斯京根模型参数估计

Parameter estimation for Muskingum routing model based on immune clonal selection algorithm

针对马斯京根河道洪水演算模型参数估计中所存在的线性化、求解复杂、精度差等问题,提出了一种基于免疫克隆选择算法(ICSA)的马斯京根模型参数估计新方法。实验和应用结果表明,基于免疫克隆选择的马斯京根模型参数估计算法具有求解速度快,计算精度高,算法控制参数设置简便、通用性强等特点,与现有的马斯京根模型参数估计方法相比,该算法显示出更好的优化性能,能够很好地解决马斯京根模型的参数最优估计问题,从而为马斯京根模型参数的估计提供了一种新的更为有效的方法。该算法也可广泛应用于其他洪水预报模型的优化问题。

In view of the nonlinearity and complexity of Muskingum flood routing model, a new method of parameter estimation for Muskingtun routing model based on Immune Clonal Selection Algorithm（ICSA） is proposed in this paper.The resuits of simulation experiment and application show that ICSA has many good properties such as fast computing speed,high accuracy, easy control variables setting,high universality and etc.Compared with the other parameter estimation methods of Muskingum routing model,ICSA has the best performance.So ICSA can be used as an efficient method for parameter estimation of Muskingum routing model, furthermore,it can be widely applied to optimize varieties of flood forecast model.