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A review on machine learning, artificial intelligence, and smart technology in water treatment and monitoring
Artificial-intelligence methods and machine-learning models have demonstrated their ability
to optimize, model, and automate critical water-and wastewater-treatment applications …
to optimize, model, and automate critical water-and wastewater-treatment applications …
Predicting water quality with artificial intelligence: a review of methods and applications
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 …
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)
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 …
sources. Concurrently, a water quality index (WQI) requires some water quality parameters …
[HTML][HTML] Machine learning models for water quality prediction: a comprehensive analysis and uncertainty assessment in Mirpurkhas, Sindh, Pakistan
Groundwater represents a pivotal asset in conserving natural water reservoirs for potable
consumption, irrigation, and diverse industrial uses. Nevertheless, human activities …
consumption, irrigation, and diverse industrial uses. Nevertheless, human activities …
[HTML][HTML] AI-driven modelling approaches for predicting oxygen levels in aquatic environments
Reliable water quality models are crucial for better water management and pollution control.
Biochemical oxygen demand (BOD) and dissolved oxygen (DO) are the widely recognized …
Biochemical oxygen demand (BOD) and dissolved oxygen (DO) are the widely recognized …
Applications of IoT and artificial intelligence in water quality monitoring and prediction: A review
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 …
time data that can be viewed and interpreted via a visual format supported by a server …
Comparison of machine learning algorithms to predict dissolved oxygen in an urban stream
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 …
impacts. This study sought to identify a successful predictive machine learning model with …
Using hysteresis to predict the charge recombination properties of perovskite solar cells
The mixed halide perovskites have become famous worldwide due to their rapid
development of power conversion efficiency (PCE) and unique photoelectric properties …
development of power conversion efficiency (PCE) and unique photoelectric properties …
Prediction of total organic carbon and E. coli in rivers within the Milwaukee River basin using machine learning methods
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 …
point sources and non-point sources, including organic matter pollution and fecal bacterial …
The potential of big data and machine learning for ground water quality assessment and prediction
Water, a priceless gift from nature, acts as Earth's matrix, medium, and life-sustaining
substance. While the planet is predominantly covered by water, only 3% is available as …
substance. While the planet is predominantly covered by water, only 3% is available as …