Journal
WATER RESOURCES MANAGEMENT
Volume 30, Issue 8, Pages 2767-2783Publisher
SPRINGER
DOI: 10.1007/s11269-016-1321-y
Keywords
Nonlinear Muskingum model; Parameter identification; Backtracking search algorithm; Flood routing; Wilcoxon signed ranks test
Categories
Funding
- National Natural Science Foundation of China [51379080, 41571514]
Ask authors/readers for more resources
Nonlinear Muskingum model is a popular approach widely used for flood routing in hydraulic engineering. An improved backtracking search algorithm (BSA) is proposed to estimate the parameters of nonlinear Muskingum model. The orthogonal designed initialization population strategy and chaotic sequences are introduced to improve the exploration and exploitation ability of BSA. At the same time, a selection strategy based individual feasibility violation is developed to ensure that the computed outflows are non-negative in the evolutionary process. Finally, three examples are employed to demonstrate the performance of the improved BSA. The comparison between the results of routing outflows and those of Wilcoxon signed ranks test shows that the improved BSA outperforms particle swarm optimization, genetic algorithm, differential evolution and other algorithms reported in the literature in terms of solution quality. Therefore, it is reasonable to draw the conclusion that the proposed BSA is a satisfactory and efficient choice for parameter estimation of nonlinear Muskingum model.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available