Recent advances in surface water quality prediction using artificial intelligence models

Q Zhang, X You - Water Resources Management, 2024 - Springer
Accurate water quality prediction plays a vital role in sustainable water management. The
artificial intelligence models commonly used in water management including artificial neural …

Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index

SI Abba, QB Pham, G Saini, NTT Linh… - … Science and Pollution …, 2020 - Springer
In recent decades, various conventional techniques have been formulated around the world
to evaluate the overall water quality (WQ) at particular locations. In the present study, back …

Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment

SD Latif - Environmental Science and Pollution Research, 2021 - Springer
One of the most critical parameters in concrete design is compressive strength. As the
compressive strength of concrete is correctly measured, time and cost can be decreased …

The Potential of Big Data and Machine Learning for Ground Water Quality Assessment and Prediction

A Rajeev, R Shah, P Shah, M Shah… - Archives of Computational …, 2024 - Springer
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 …

[HTML][HTML] An ensembled method for predicting dissolved oxygen level in aquaculture environment

D Feng, Q Han, L Xu, F Sohel, SG Hassan, S Liu - Ecological Informatics, 2024 - Elsevier
Dissolved oxygen (DO) level is an important indicator aquaculture quality. This study
proposes an ensembled method, WTD-GWO-SVR, combining wavelet threshold denoising …

[HTML][HTML] Integrated machine learning–based model and WQI for groundwater quality assessment: ML, geospatial, and hydro-index approaches

SAA El-Magd, IS Ismael, MAS El-Sabri… - … Science and Pollution …, 2023 - ncbi.nlm.nih.gov
The demands upon the arid area for water supply pose threats to both the quantity and
quality of social and economic activities. Thus, a widely used machine learning model …

Integrated machine learning–based model and WQI for groundwater quality assessment: ML, geospatial, and hydro-index approaches

SA Abu El-Magd, IS Ismael, MAS El-Sabri… - … Science and Pollution …, 2023 - Springer
The demands upon the arid area for water supply pose threats to both the quantity and
quality of social and economic activities. Thus, a widely used machine learning model …

Smart system for water quality monitoring utilizing long-range-based Internet of Things

MA Murti, ARA Saputra, I Alinursafa, AN Ahmed… - Applied Water …, 2024 - Springer
Water is the most basic need for humans and a source of livelihood for humans. Lack of
human awareness to maintain water quality, causing water to become polluted, by both …

Intelligent data analytics approaches for predicting dissolved oxygen concentration in river: extremely randomized tree versus random forest, MLPNN and MLR

S Heddam - Intelligent Data Analytics for Decision-Support Systems …, 2021 - Springer
This chapter designs intelligent data analytic approaches for predicting dissolved oxygen
concentration in river utilizing extremely randomized tree versus random forest, MLPNN and …

Multiple remotely sensed datasets and machine learning models to predict chlorophyll-a concentration in the Nakdong River, South Korea

B Lee, JK Im, JW Han, T Kang, W Kim, M Kim… - … Science and Pollution …, 2024 - Springer
Abstract The Nakdong River is a crucial water resource in South Korea, supplying water for
various purposes such as potable water, irrigation, and recreation. However, the river is …