title: [Comparison of parameter optimization algorithms for environmental model].
abstract: Parameters identification is achieved through the minimization of objective function based on model outputs and the observed data. Because of ever increasing complexity of environmental-models, there are significant difficulty for conventional optimal methods to present a global optimization. On the contrast, however, direct optimization algorithms are widely developed in recent years due to increasing computer efficiency and show promising applications. Four direct optimal algorithms, i.e. CRS algorithm, SCE UA algorithm, SA algorithm and Annealing-Simplex algorithm, were thus selected in this paper to compare their performances via case studies.
authors.affiliation: Environmental Simulation and Pollution Control State Key Joint Laboratory, Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084.
authors.forename: Liu
authors.initials: L
authors.lastname: Yi
authors.forename: Jining
authors.initials: J
authors.lastname: Chen
authors.forename: Pengfei
authors.initials: P
authors.lastname: Du
mesh_terms: D000465:Algorithms; D004777:Environment