[HTML][HTML] A review of the application of machine learning in water quality evaluation
M Zhu, J Wang, X Yang, Y Zhang, L Zhang… - Eco-Environment & …, 2022 - Elsevier
With the rapid increase in the volume of data on the aquatic environment, machine learning
has become an important tool for data analysis, classification, and prediction. Unlike …
has become an important tool for data analysis, classification, and prediction. Unlike …
[HTML][HTML] The role of deep learning in urban water management: A critical review
Deep learning techniques and algorithms are emerging as a disruptive technology with the
potential to transform global economies, environments and societies. They have been …
potential to transform global economies, environments and societies. They have been …
Machine learning: new ideas and tools in environmental science and engineering
The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …
in the field of environmental science and engineering (ESE) demands accompanied …
A comprehensive review of deep learning applications in hydrology and water resources
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume,
variety and velocity of water-related data are increasing due to large-scale sensor networks …
variety and velocity of water-related data are increasing due to large-scale sensor networks …
Recent advances in artificial intelligence and machine learning for nonlinear relationship analysis and process control in drinking water treatment: A review
L Li, S Rong, R Wang, S Yu - Chemical Engineering Journal, 2021 - Elsevier
Because of its robust autonomous learning and ability to address complex problems,
artificial intelligence (AI) has increasingly demonstrated its potential to solve the challenges …
artificial intelligence (AI) has increasingly demonstrated its potential to solve the challenges …
A review of leakage detection strategies for pressurised pipeline in steady-state
Pipeline and pipe networks are the most environmentally sustainable and energy-efficient
means for transportation and distribution of fluids of high social and commercial value like …
means for transportation and distribution of fluids of high social and commercial value like …
Machine learning framework for intelligent aeration control in wastewater treatment plants: Automatic feature engineering based on variation sliding layer
Intelligent control of wastewater treatment plants (WWTPs) has the potential to reduce
energy consumption and greenhouse gas emissions significantly. Machine learning (ML) …
energy consumption and greenhouse gas emissions significantly. Machine learning (ML) …
[HTML][HTML] Leakage detection in water distribution networks via 1D CNN deep autoencoder for multivariate SCADA data
HM Tornyeviadzi, R Seidu - Engineering Applications of Artificial …, 2023 - Elsevier
Leakages are undesirable events in water distribution networks (WDNs) with mostly
unknown incident time making it extremely difficult to accurately label leaks in distribution …
unknown incident time making it extremely difficult to accurately label leaks in distribution …
Review of model-based and data-driven approaches for leak detection and location in water distribution systems
Z Hu, B Chen, W Chen, D Tan, D Shen - Water Supply, 2021 - iwaponline.com
Leak detection and location in water distribution systems (WDSs) is of utmost importance for
reducing water loss, which is, however, a major challenge for water utility companies. To this …
reducing water loss, which is, however, a major challenge for water utility companies. To this …
A hybrid model for streamflow forecasting in the basin of euphrates
HC Kilinc, B Haznedar - Water, 2022 - mdpi.com
River flow modeling plays a crucial role in water resource management and ensuring its
sustainability. Therefore, in recent years, in addition to the prediction of hydrological …
sustainability. Therefore, in recent years, in addition to the prediction of hydrological …