A survey of machine learning methods applied to anomaly detection on drinking-water quality data-Reference-Cited by-同舟云学术

A survey of machine learning methods applied to anomaly detection on drinking-water quality data

Published:2019-03-16 Issue:3 Volume:16 Page:235-248
ISSN:1573-062X
Container-title:Urban Water Journal
language:en
Short-container-title:Urban Water Journal

Author:

Dogo Eustace M.¹^ORCID,Nwulu Nnamdi I.²^ORCID,Twala Bhekisipho³^ORCID,Aigbavboa Clinton⁴^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering Science, Institute for Intelligent Systems, University of Johannesburg, Johannesburg, South Africa

2. Department of Electrical and Electronics Engineering Science, University of Johannesburg, Johannesburg, South Africa

3. Department of Electrical and Mining Engineering, University of South Africa, Pretoria, South Africa

4. Department of Construction Management and Quantity Surveying, University of Johannesburg, Johannesburg, South Africa

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/1573062X.2019.1637002

Reference87 articles.

1. Data analysis and outlier detection in smart city

2. Water Quality Monitoring Using Wireless Sensor Networks

3. A survey of network anomaly detection techniques

4. Application of Artificial Bee Colony algorithm in TEC seismo-ionospheric anomalies detection

5. Wireless sensor networks: a survey

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