A review on machine learning, artificial intelligence, and smart technology in water treatment and monitoring

M Lowe, R Qin, X Mao - Water, 2022 - mdpi.com
Artificial-intelligence methods and machine-learning models have demonstrated their ability
to optimize, model, and automate critical water-and wastewater-treatment applications …

Predicting water quality with artificial intelligence: a review of methods and applications

D Irwan, M Ali, AN Ahmed, G Jacky, A Nurhakim… - … Methods in Engineering, 2023 - Springer
The water is the main pivotal sources of irrigation in agricultural activities and affects human
daily activities such as drinking. The water quality has a significant impact on various …

Performance of machine learning methods in predicting water quality index based on irregular data set: application on Illizi region (Algerian southeast)

S Kouadri, A Elbeltagi, ARMT Islam, S Kateb - Applied Water Science, 2021 - Springer
Groundwater quality appraisal is one of the most crucial tasks to ensure safe drinking water
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …

Applications of IoT and artificial intelligence in water quality monitoring and prediction: A review

HM Mustafa, A Mustapha, G Hayder… - 2021 6th international …, 2021 - ieeexplore.ieee.org
Currently, internet of things (IoT) devices like environmental sensors are used to capture real-
time data that can be viewed and interpreted via a visual format supported by a server …

Using hysteresis to predict the charge recombination properties of perovskite solar cells

J Wu, Y Li, Y Li, W Xie, J Shi, D Li, S Cheng… - Journal of Materials …, 2021 - pubs.rsc.org
The mixed halide perovskites have become famous worldwide due to their rapid
development of power conversion efficiency (PCE) and unique photoelectric properties …

Comparison of machine learning algorithms to predict dissolved oxygen in an urban stream

MM Bolick, CJ Post, MZ Naser… - Environmental Science and …, 2023 - Springer
Water quality monitoring for urban watersheds is critical to identify the negative urbanization
impacts. This study sought to identify a successful predictive machine learning model with …

[HTML][HTML] Machine learning models for water quality prediction: a comprehensive analysis and uncertainty assessment in Mirpurkhas, Sindh, Pakistan

F Abbas, Z Cai, M Shoaib, J Iqbal, M Ismail, AF Alrefaei… - Water, 2024 - mdpi.com
Groundwater represents a pivotal asset in conserving natural water reservoirs for potable
consumption, irrigation, and diverse industrial uses. Nevertheless, human activities …

Prediction of total organic carbon and E. coli in rivers within the Milwaukee River basin using machine learning methods

N Nafsin, J Li - Environmental Science: Advances, 2023 - pubs.rsc.org
Urban water undergoes physical and chemical changes due to various contaminants from
point sources and non-point sources, including organic matter pollution and fecal bacterial …

[HTML][HTML] Water quality predictive analytics using an artificial neural network with a graphical user interface

NNM Rizal, G Hayder, KA Yusof - Water, 2022 - mdpi.com
Since clean water is well known as one of the crucial sources that all living things need in
their daily lives, the demand for clean freshwater nowadays has increased. However, water …

Modelling of river flow using particle swarm optimized cascade-forward neural networks: A case study of Kelantan River in Malaysia

G Hayder, MI Solihin, HM Mustafa - Applied Sciences, 2020 - mdpi.com
Water resources management in Malaysia has become a crucial issue of concern due to its
role in the economic and social development of the country. Kelantan river (Sungai …