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论文类型：期刊论文

发表时间：2015-09-15

发表刊物：MARINE POLLUTION BULLETIN

收录刊物：SCIE、EI、PubMed、Scopus

卷号：98

期号：1-2

页面范围：137-147

ISSN号：0025-326X

关键字：Data-driven method; Water quality model; Function approximation; Parameter optimization

摘要：Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB). (C) 2015 Elsevier Ltd. All rights reserved.