AIMC Topic: Water Quality

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Research progress in water quality prediction based on deep learning technology: a review.

Environmental science and pollution research international
Water, an invaluable and non-renewable resource, plays an indispensable role in human survival and societal development. Accurate forecasting of water quality involves early identification of future pollutant concentrations and water quality indices,...

Development of AI-based hybrid soft computing models for prediction of critical river water quality indicators.

Environmental science and pollution research international
Prediction of river water quality indicators (RWQIs) using artificial intelligence (AI)-based hybrid soft computing modeling techniques could provide essential predictions required for efficient river health planning and management. The study describ...

A hybrid prediction model of dissolved oxygen concentration based on secondary decomposition and bidirectional gate recurrent unit.

Environmental geochemistry and health
Dissolved oxygen is one of the important comprehensive indicators of river water quality, which reflects the degree of pollution in the water body. Monitoring and predicting dissolved oxygen are an important tool for water quality management, which h...

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 ...

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...

Comparing ARIMA and various deep learning models for long-term water quality index forecasting in Dez River, Iran.

Environmental science and pollution research international
Water scarcity poses a significant global challenge, particularly in developing nations like Iran. Consequently, there is a pressing requirement for ongoing monitoring and prediction of water quality, utilizing advanced techniques characterized by lo...

>Water quality prediction of artificial intelligence model: a case of Huaihe River Basin, China.

Environmental science and pollution research international
Accurate prediction of water quality contributes to the intelligent management of water resources. Water quality indices have time series characteristics and nonlinearity, but the existing models only focus on the forward time series when long short-...

Machine learning predicts which rivers, streams, and wetlands the Clean Water Act regulates.

Science (New York, N.Y.)
We assess which waters the Clean Water Act protects and how Supreme Court and White House rules change this regulation. We train a deep learning model using aerial imagery and geophysical data to predict 150,000 jurisdictional determinations from the...

Detection and prediction of pathogenic microorganisms in aquaculture (Zhejiang Province, China).

Environmental science and pollution research international
The detection and prediction of pathogenic microorganisms play a crucial role in the sustainable development of the aquaculture industry. Currently, researchers mainly focus on the prediction of water quality parameters such as dissolved oxygen for e...

A hybrid deep learning approach to improve real-time effluent quality prediction in wastewater treatment plant.

Water research
Wastewater treatment plant (WWTP) operation is usually intricate due to large variations in influent characteristics and nonlinear sewage treatment processes. Effective modeling of WWTP effluent water quality can provide valuable decision-making supp...