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- W2350417801 abstract "An application of multi-objective particle swarm optimization(MOPSO) algorithm for optimization of the hydrological model(HYMOD) is presented in this paper.MOPSO algorithm is used to find non-dominated solutions with two objectives: high flow Nash-Sutcliffe efficiency and low flow Nash-Sutcliffe efficiency.The two sets' coverage rate and Pareto front spacing metric are two criterions to analyze the performance of the algorithms.MOPSO algorithm surpasses multi-objective shuffled complex evolution metropolis(MOSCEM_UA) algorithm in terms of the two sets' coverage rate.But when we come to Pareto front spacing rate,the non-dominated solutions of MOSCEM_UA algorithm are better-distributed than that of MOPSO algorithm when the iteration is set to 40000.In addition,there are obvious conflicts between the two objectives.But a compromise solution can be acquired by adopting the MOPSO algorithm." @default.
- W2350417801 created "2016-06-24" @default.
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- W2350417801 date "2011-01-01" @default.
- W2350417801 modified "2023-09-27" @default.
- W2350417801 title "Optimization of the Hydrological Model Using Multi-objective Particle Swarm Optimization Algorithm" @default.
- W2350417801 hasPublicationYear "2011" @default.
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