A novel comprehensive framework for analyzing and assessing water quality and failure consequences based on Bayesian networks-Reference-Cited by-同舟云学术

A novel comprehensive framework for analyzing and assessing water quality and failure consequences based on Bayesian networks

Published:2020-09-16 Issue:5 Volume:93 Page:738-749
ISSN:1061-4303
Container-title:Water Environment Research
language:en
Short-container-title:Water Environment Research

Author:

Zerouali Bilal¹²^ORCID,Zerouali Bilel³^ORCID

Affiliation:

1. Petrochemical and Process Engineering Department 20 August 1955 University of Skikda Skikda Algeria

2. Laboratoire de Génie Electromécanique LGEM Badji Mokhtar University Annaba Algeria

3. Research Laboratory of Water Resources, Soil and Environment Department of Civil Engineering Faculty of Civil Engineering and Architecture Amar Telidji University Laghouat Algeria

Publisher

Wiley

Subject

Water Science and Technology,Ecological Modelling,Waste Management and Disposal,Pollution,Environmental Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wer.1450

Reference29 articles.

1. Potential effects of groundwater and surface water contamination in an urban area, Qus City, Upper Egypt

2. Agena‐Risk Software Version 7.0. (2020). Retrieved fromhttps://www.agenarisk.com/

3. Safety analysis of offshore decommissioning operation through Bayesian network

4. Enhancement of the free residual chlorine concentration at the ends of the water supply network: Case study of Souk Ahras city – Algeria

5. Economic analysis of drinking water services, case of the city of Souk-Ahras (Algeria)

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