| 篇名： | Parameters estimation of river water quality model using a differential evolution algorithm | 论文类型： | SCI |
| 刊名： | Fresenius Environmental Bulletin 2018,2(27) |
| 作者： | Hongqin Xue | 发表时间： | 2018-02-22 |
| 关键词： | Differential evolution (DE), Parameter estimation | PDF文档： | 查看/下载 |
| 摘要： | To avoid the shortcomings of traditional optimization algorithms, a new multi-parameters estimation model based on Differential Evolution(DE) algorithm coupled with water quality model was proposed in this paper. The computational results of three numerical cases indicate the proposed parameter estimation model has high accuracy and good anti-noise properties. It can give precise results under both steady flow and unsteady flow. It can be used to identify parameters for both 1D and 2D water quality model, including analytical solution model and numerical model. Comparison results show that the method based on DE has roughly same accuracy as that on GA, but has higher convergence speed and better anti-noise property. This work contributes to the parameter estimation for river systems. |
