干旱区生态环境知识资源中心(Arid): Water Quality Classification and Machine Learning Model for Predicting Water Quality Status-A Study on Loa River Located in an Extremely Arid Environment: Atacama Desert

Arid

DOI	10.3390/w15162868
	Water Quality Classification and Machine Learning Model for Predicting Water Quality Status-A Study on Loa River Located in an Extremely Arid Environment: Atacama Desert
	Flores, Victor; Bravo, Ingrid; Saavedra, Marcelo
通讯作者	Flores, V
来源期刊	WATER
EISSN	2073-4441
出版年	2023
卷号	15 期号:16
英文摘要	Water is the most important resource for human, animal, and vegetal life. Recently, the use of artificial intelligence techniques, such as Random Forest, has been combined with other techniques, such as models of logical-mathematical reasoning, to generate predictive water quality models. In this study, a rule-based inference technique to generate water quality labels is described, using historical physicochemical parameter data on seven water monitoring stations in Loa River, collected by the Chilean Ministry of the Environment. Next, a predictive model of water quality status was created, using Random Forest, physicochemical parameters, and expert knowledge. The validation of Random Forest results is described using three quality indicators from the machine learning model: accuracy (acc), precision (p), and recall (r). This paper describes dataset preparation, the refinement of the threshold values used for the physicochemical parameters most significant in the class, and the predictive model labeling water quality. The models obtained yielded the following mean values: acc = 0.897, p = 89.73, and r = 0.928. The ML model reported here is novel since no previous studies of this kind predict the water quality of Loa River, located in an extremely arid zone. This study also helps to create specific knowledge to predict freshwater quality.
英文关键词	river water quality machine learning random forest pollution characteristics arid regions
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:001056774500001
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/399059
推荐引用方式 GB/T 7714	Flores, Victor,Bravo, Ingrid,Saavedra, Marcelo. Water Quality Classification and Machine Learning Model for Predicting Water Quality Status-A Study on Loa River Located in an Extremely Arid Environment: Atacama Desert[J],2023,15(16).
APA	Flores, Victor,Bravo, Ingrid,&Saavedra, Marcelo.(2023).Water Quality Classification and Machine Learning Model for Predicting Water Quality Status-A Study on Loa River Located in an Extremely Arid Environment: Atacama Desert.WATER,15(16).
MLA	Flores, Victor,et al."Water Quality Classification and Machine Learning Model for Predicting Water Quality Status-A Study on Loa River Located in an Extremely Arid Environment: Atacama Desert".WATER 15.16(2023).