Modeling chlorophyll-a concentrations using an artificial neural network for precisely eco-restoring lake basin

doi:10.1016/j.ecoleng.2016.06.072

	Modeling chlorophyll-a concentrations using an artificial neural network for precisely eco-restoring lake basin
	Lu, Fang 1; Chen, Zhi 1; Liu, Wenquan 2; Shao, Hongbo 3
刊名	ECOLOGICAL ENGINEERING
	2016-10
卷号	95 页码:422-429
关键词	Back-propagation artificial neural network Chlorophyll-a Prediction Lake water quality Eco-restoring
ISSN号	0925-8574
DOI	10.1016/j.ecoleng.2016.06.072
英文摘要	A back-propagation artificial neural network (BPANN) model was developed in this study for the prediction of chlorophyll-a concentration in Lake Champlain. 21 years of monitoring data (1992-2012) of water quality parameters was used to train, validate and test the BPANN models. The optimal input parameters of the model were selected on the basis of the performance of models built with different combinations of input variables. To verify the model performances, the trained models were applied to field monitoring data from Lake Champlain. Prediction accuracy was measured by using the coefficient of determination (R-2) and RMSE-observations standard deviation ratio (RSR). The R-2 values of the best-performed model in the training set, validation set, testing set, and all-year data were 0.82, 0.93, 0.81, and 0.87, respectively. The corresponding RSR values of the three data sets and all-year were 0.62, 0.38, 0.53, and 0.48, respectively. Results indicated that the developed BPANN model can predict chlorophyll-a concentrations in Lake Champlain with high accuracy and provide a quick assessment of chlorophyll-a variation for lake management and eco-restoration. (C) 2016 Elsevier B.V. All rights reserved.
资助项目	Scientific Research Fund of the First Institute of Oceanography, SOA[2015T01]
WOS关键词	WATER-QUALITY ; CYANOBACTERIAL BLOOMS ; ALGAL BLOOMS ; RIVER ; PREDICTION ; TEMPERATURE ; RESOURCES ; CHAMPLAIN ; VARIABLES
WOS研究方向	Environmental Sciences & Ecology ; Engineering
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000385371400048
内容类型	期刊论文
源URL	[http://ir.fio.com.cn:8080/handle/2SI8HI0U/26487]
专题	自然资源部第一海洋研究所
通讯作者	Liu, Wenquan; Shao, Hongbo
作者单位	1.Concordia Univ, Dept Bldg Civil & Environm Engn, Montreal, PQ H3G 1M8, Canada 2.SOA, Inst Oceanog 1, Key Lab Marine Sedimentol & Environm Geol, Qingdao 266061, Peoples R China 3.Jiangsu Acad Agr Sci, Inst Agrobiotechnol, Nanjing 210014, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Lu, Fang,Chen, Zhi,Liu, Wenquan,et al. Modeling chlorophyll-a concentrations using an artificial neural network for precisely eco-restoring lake basin[J]. ECOLOGICAL ENGINEERING,2016,95:422-429.
APA	Lu, Fang,Chen, Zhi,Liu, Wenquan,&Shao, Hongbo.(2016).Modeling chlorophyll-a concentrations using an artificial neural network for precisely eco-restoring lake basin.ECOLOGICAL ENGINEERING,95,422-429.
MLA	Lu, Fang,et al."Modeling chlorophyll-a concentrations using an artificial neural network for precisely eco-restoring lake basin".ECOLOGICAL ENGINEERING 95(2016):422-429.