AIMC Topic: Water Supply
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Fuzzy multi-objective optimization for sustainable agricultural water management of irrigation networks.
Journal of environmental management
Nov 20, 2024
Sustainable water resource management in arid and water deficit regions requires optimal use of water resources due to competition among different water sectors. The purpose of this study is to model uncertainties in economic and hydro-climatic varia...
Explainable artificial intelligence for reliable water demand forecasting to increase trust in predictions.
Water research
Nov 9, 2024
The "EU Artificial Intelligence Act" sets a framework for the implementation of artificial intelligence (AI) in Europe. As a legal assessment reveals, AI applications in water supply systems are categorised as high-risk AI if a failure in the AI appl...
Acoustic leak localization for water distribution network through time-delay-based deep learning approach.
Water research
Oct 9, 2024
Water leakage within water distribution networks (WDNs) presents significant challenges, encompassing infrastructure damage, economic losses, and public health risks. Traditional methods for leak localization based on acoustic signals encounter inher...
Integrated water resource management in the Segura Hydrographic Basin: An artificial intelligence approach.
Journal of environmental management
Oct 1, 2024
Managing resources effectively in uncertain demand, variable availability, and complex governance policies is a significant challenge. This paper presents a paradigmatic framework for addressing these issues in water management scenarios by integrati...
Development of a machine learning model to support low cost real-time Legionella monitoring in premise plumbing systems.
Water research
Sep 30, 2024
Legionella pneumophila (L. pneumophila) is a pathogenic bacterium primarily known for causing Legionnaires' Disease which is known for high mortality rates, particularly in the elderly. With caseloads continuing to increase, further research is neede...
Predicting the performance of lithium adsorption and recovery from unconventional water sources with machine learning.
Water research
Sep 7, 2024
Selective lithium (Li) recovery from unconventional water sources (UWS) (e.g., shale gas waters, geothermal brines, and rejected seawater desalination brines) using inorganic lithium-ion sieve (LIS) materials can address Li supply shortages and distr...
Forecasting for Haditha reservoir inflow in the West of Iraq using Support Vector Machine (SVM).
PloS one
Sep 6, 2024
Accurate inflow forecasting is an essential non-engineering strategy to guarantee flood management and boost the effectiveness of the water supply. As inflow is the primary reservoir input, precise inflow forecasting may also offer appropriate reserv...
Machine learning for environmental justice: Dissecting an algorithmic approach to predict drinking water quality in California.
The Science of the total environment
Aug 24, 2024
The potential for machine learning to answer questions of environmental science, monitoring, and regulatory enforcement is evident, but there is cause for concern regarding potential embedded bias: algorithms can codify discrimination and exacerbate ...
Determinants of adoption of household water treatment in Haiti using two analysis methods: logistic regression and machine learning.
Journal of water and health
Aug 21, 2024
Household water treatment (HWT) is recommended when safe drinking water is limited. To understand determinants of HWT adoption, we conducted a cross-sectional survey with 650 households across different regions in Haiti. Data were collected on 71 dem...
Exploring the potential of machine learning to understand the occurrence and health risks of haloacetic acids in a drinking water distribution system.
The Science of the total environment
Aug 15, 2024
Determining the occurrence of disinfection byproducts (DBPs) in drinking water distribution system (DWDS) remains challenging. Predicting DBPs using readily available water quality parameters can help to understand DBPs associated risks and capture t...
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