Forecasting point-of-consumption chlorine residual in refugee settlements using ensembles of artificial neural networks

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  • Dan Campbell University of North Carolina-Chapel Hill Water Institute Email: dcampbell@unc.edu
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Forecasting point-of-consumption chlorine residual in refugee settlements using ensembles of artificial neural networks

Dear Colleagues:

An important study from Syed Imran Ali:

Forecasting point-of-consumption chlorine residual in refugee settlements using ensembles of artificial neural networks . npj Clean Water, June 2021. This paper establishes the basis for the machine-learning analytics used in the  Safe Water Optimization Tool , a new web-based tool that helps aid workers generate evidence-based and site-specific water chlorination targets for ensuring household water safety in refugee/IDP settlements. Based on our read of the literature, we believe this is one of the first concrete applications of an AI technology in the emergency WASH space.  

Syed Imran Ali, PhD  
Lead, Safe Water Optimization Tool 
Research Fellow, Dahdaleh Institute for Global Health Research 
Adjunct Professor, Lassonde School of Engineering 
York University, Toronto, Canada 
e:  siali@yorku.ca   |  t: [url=http://416-434-0192/]416-434-0192[/url]  
Dan Campbell, Knowledge Management Specialist
University of North Carolina-Chapel Hill
Water Institute
USA
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