马斯京根模型参数估计的差分进化算法

针对洪水演算的马斯京根模型参数估计问题，首先将其归结为非线性参数优化问题，然后利用自适应加速差分进化算法进行求解。计算结果表明，自适应加速差分进化算法具有求解速度快、计算精度高、算法控制参数设置简便、通用性强等优点，与现有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，从而为准确估计马斯京根模型参数提供了一种更为有效的方法。该算法也可以广泛应用于其他各种复杂非线性模型的优化问题，特别是在洪水预报方面有很好的应用前景。

Differential Evolution for Parameter Estimation of Muskingum Model

For the parameter estimation problem of flood calculation of Muskingum model,first,it is summed up as a non-linear parameter optimization problem,and then solved by adaptive accelerating differential evolution(AADE).The results form application of AADE in estimating parameter of Muskingum model show that AADE has many good properties such as fast computing speed,high accuracy,easy control variables setting,high universality and etc.Compared with other optimization estimation methods of Muskingum model,AADE ...