气候变化领域集成服务门户(CCPortal): Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning

CCPortal

DOI	10.1016/j.jenvman.2024.120394
	Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning
	Cui, Hao; Tao, Yiwen; Li, Jian; Zhang, Jinhui; Xiao, Hui; Milne, Russell
发表日期	2024
ISSN	0301-4797
EISSN	1095-8630
起始页码	354
卷号	354
英文摘要	Algal blooms, exacerbated by climate change and eutrophication, have emerged as a global concern. In this study, we introduce a novel interpretable machine learning (ML) workflow tailored for investigating the dynamics of algal populations in grass -type lakes, Liangzi lake. Utilizing seven ML methods and incorporating the covariance matrix adaptation evolution strategy (CMA-ES), we predict algal density across three distinct time periods, resulting in the construction of a total of 30 ML models. The CMA-ES-CatBoost model consistently demonstrates superior predictive accuracy and generalization capability across these periods. Through the collective validation of various interpretable tools, we identify water temperature and permanganate index as the two most critical water quality parameters (WQIs) influencing algal density in Liangzi Lake. Additionally, we quantify the independent and interactive effects of WQIs on algal density, pinpointing key thresholds and trends. Furthermore, we determine the minimum combination of WQIs that achieves near -optimal predictive performance, striking a balance between accuracy and cost-effectiveness. These findings offer a scientific and economically efficient foundation for governmental agencies to formulate strategies for water quality management and sustainable development.
英文关键词	Algal population dynamics; Water quality; Machine learning; Explainable AI; Grass -type lake
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Sciences
WOS记录号	WOS:001194279700001
来源期刊	JOURNAL OF ENVIRONMENTAL MANAGEMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/294169
作者单位	Zhengzhou University; Zhengzhou University; Zhongyuan University of Technology; Saint Marys University - Canada; University of Alberta
推荐引用方式 GB/T 7714	Cui, Hao,Tao, Yiwen,Li, Jian,et al. Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning[J],2024,354.
APA	Cui, Hao,Tao, Yiwen,Li, Jian,Zhang, Jinhui,Xiao, Hui,&Milne, Russell.(2024).Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning.JOURNAL OF ENVIRONMENTAL MANAGEMENT,354.
MLA	Cui, Hao,et al."Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning".JOURNAL OF ENVIRONMENTAL MANAGEMENT 354(2024).