An integrated data-driven framework for surface water quality anomaly detection and early warning-Reference-Cited by-同舟云学术

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An integrated data-driven framework for surface water quality anomaly detection and early warning

Published:2020-04 Issue: Volume:251 Page:119145
ISSN:0959-6526
Container-title:Journal of Cleaner Production
language:en
Short-container-title:Journal of Cleaner Production

Author:

Liu Jie,Wang Peng,Jiang Dexun,Nan Jun,Zhu Weiyu

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Youth Doctoral Scientific Research Staring Foundation of Harbin University

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Strategy and Management,General Environmental Science,Renewable Energy, Sustainability and the Environment

Reference38 articles.

1. A dynamic thresholds scheme for contaminant event detection in water distribution systems;Arad;Water Res.,2013

2. Anomaly detection and reliability analysis of groundwater by crude Monte Carlo and importance sampling approaches;Azimi;Water Resour. Manag.,2018

3. Construction of confidence regions in the roc space after the estimation of the optimal Youden index-based cut-off point;Bantis;Biometrics,2014

4. Extreme events, water quality and health: a participatory Bayesian risk assessment tool for managers of reservoirs;Bertone;J. Clean. Prod.,2016

5. LOF: identifying density-based local outliers;Breunig;ACM SIGMOD International Conference on Management of Data,2000

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