气候变化领域集成服务门户(CCPortal): Bayesian network reasoning and machine learning with multiple data features: air pollution risk monitoring and early warning

CCPortal

DOI	10.1007/s11069-021-04504-3
	Bayesian network reasoning and machine learning with multiple data features: air pollution risk monitoring and early warning
	Xie X.; Zuo J.; Xie B.; Dooling T.A.; Mohanarajah S.
发表日期	2021
ISSN	0921030X
起始页码	2555
结束页码	2572
卷号	107 期号:3
英文摘要	From a macro-perspective, based on machine learning and data-driven approach, this paper utilizes multi-featured data from 31 provinces and regions in China to build a Bayesian network (BN) analysis model for predicting air quality index and warning the air pollution risk at the city level. Further, a two-layer BN for analyzing influencing factors of various air pollutants is developed. Subsequently, the model is applied to forecast the trends of temporal and spatial changes in the form of probabilistic inference and to investigate the degree of impact incurred from individual influencing factors. From the comparisons with the results obtained from other machine learning approaches and algorithms such as neural networks, it is concluded that by comprehensively using the established BN, one can not only reach a monitoring and early warning accuracy rate of 90% but also scrutinize and diagnose the main cause of air pollution risk changes from the perspective of probability. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
关键词	Air pollution risk AQI prediction Bayesian network Machine learning Statistical analysis
英文关键词	accuracy assessment; algorithm; artificial neural network; atmospheric pollution; Bayesian analysis; comparative study; early warning system; machine learning; pollution monitoring; probability; risk assessment; China
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206675
作者单位	College of Mathematics and Statistics, Hunan University of Technology and Business, Changsha, 410205, China; Institute of Big Data and Internet Innovation, Hunan University of Technology and Business, Changsha, 410205, China; Key Laboratory of Hunan Province for Statistical Learning and Intelligent Computation, Hunan University of Technology and Business, Changsha, 410205, China; Department of Chemistry and Physics, University of North Carolina At Pembroke, Pembroke, NC 28372, United States; Department of Mathematics and Computer Science, University of North Carolina At Pembroke, Pembroke, NC 28372, United States
推荐引用方式 GB/T 7714	Xie X.,Zuo J.,Xie B.,et al. Bayesian network reasoning and machine learning with multiple data features: air pollution risk monitoring and early warning[J],2021,107(3).
APA	Xie X.,Zuo J.,Xie B.,Dooling T.A.,&Mohanarajah S..(2021).Bayesian network reasoning and machine learning with multiple data features: air pollution risk monitoring and early warning.Natural Hazards,107(3).
MLA	Xie X.,et al."Bayesian network reasoning and machine learning with multiple data features: air pollution risk monitoring and early warning".Natural Hazards 107.3(2021).