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Water Supply

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Domain-informed variational neural networks and support vector machines based leakage detection framework to augment self-healing in water distribution networks.

Water research
The reduction of water leakage is essential for ensuring sustainable and resilient water supply systems. Despite recent investments in sensing technologies, pipe leakage remains a significant challenge for the water sector, particularly in developed ...

Real-time water quality prediction in water distribution networks using graph neural networks with sparse monitoring data.

Water research
Ensuring the safety and reliability of drinking water supply requires accurate prediction of water quality in water distribution networks (WDNs). However, existing hydraulic model-based approaches for system state prediction face challenges in model ...

The insightful water quality analysis and predictive model establishment via machine learning in dual-source drinking water distribution system.

Environmental research
Dual-source drinking water distribution systems (DWDS) over single-source water supply systems are becoming more practical in providing water for megacities. However, the more complex water supply problems are also generated, especially at the hydrau...

A review of graph and complex network theory in water distribution networks: Mathematical foundation, application and prospects.

Water research
Graph theory (GT) and complex network theory play an increasingly important role in the design, operation, and management of water distribution networks (WDNs) and these tasks were originally often heavily dependent on hydraulic models. Facing the ge...

A fuzzy interval dynamic optimization model for surface and groundwater resources allocation under water shortage conditions, the case of West Azerbaijan Province, Iran.

Environmental science and pollution research international
The allocation of water in areas which face shortage of water especially during hot dry seasons is of utmost importance. This is normally affected by various factors, the management of which takes a lot of time and energy with efforts falling inferti...

A novel method for multi-pollutant monitoring in water supply systems using chemical machine vision.

Environmental science and pollution research international
Drinking water is vital for human health and life, but detecting multiple contaminants in it is challenging. Traditional testing methods are both time-consuming and labor-intensive, lacking the ability to capture abrupt changes in water quality over ...

Reconstructing transient pressures in pipe networks from local observations by using physics-informed neural networks.

Water research
Reconstructing transient states presents significant challenges, particularly within complex pipe networks. These challenges arise due to nonlinear behaviours, inherent uncertainties in the system, and limitations in data availability. This work prop...

Making Waves: Towards data-centric water engineering.

Water research
Artificial intelligence (AI) is expected to transform many scientific disciplines, with the potential to significantly accelerate scientific discovery. This perspective calls for the development of data-centric water engineering to tackle water chall...

Irrigation intelligence-enabling a cloud-based Internet of Things approach for enhanced water management in agriculture.

Environmental monitoring and assessment
Advanced sensor technology, especially those that incorporate artificial intelligence (AI), has been recognized as increasingly important in various contemporary applications, including navigation, automation, water under imaging, environmental monit...

Evaluation of water resources security in Anhui Province based on GA-BP model.

Environmental science and pollution research international
Water resources security is an important cornerstone of regional sustainable development, but the current evaluation system of water resources security is not scientific, and the measurement of safety level has not been optimized by combining algorit...