Ensemble machine learning paradigms in hydrology: A review

M Zounemat-Kermani, O Batelaan, M Fadaee… - Journal of …, 2021 - Elsevier
Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …

A survey on river water quality modelling using artificial intelligence models: 2000–2020

TM Tung, ZM Yaseen - Journal of Hydrology, 2020 - Elsevier
There has been an unsettling rise in the river contamination due to the climate change and
anthropogenic activities. Last decades' research has immensely focussed on river basin …

A review of the artificial neural network models for water quality prediction

Y Chen, L Song, Y Liu, L Yang, D Li - Applied Sciences, 2020 - mdpi.com
Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …

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 …

Application of artificial intelligence to wastewater treatment: A bibliometric analysis and systematic review of technology, economy, management, and wastewater …

L Zhao, T Dai, Z Qiao, P Sun, J Hao, Y Yang - Process Safety and …, 2020 - Elsevier
Wastewater treatment is an important step for pollutant reduction and the promotion of water
environment quality. The complexity of natural conditions, influent shock, and wastewater …

Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms …

F Bagherzadeh, MJ Mehrani, M Basirifard… - Journal of Water Process …, 2021 - Elsevier
Wastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable
and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods …

Comprehensive review on machine learning methodologies for modeling dye removal processes in wastewater

SK Bhagat, KE Pilario, OE Babalola, T Tiyasha… - Journal of Cleaner …, 2023 - Elsevier
A wide range of dyes are being disposed in water bodies from several industrial runoff and
the quantity is rapidly increasing over the years. From an environmental safety point of view …

A review of artificial intelligence in water purification and wastewater treatment: Recent advancements

S Safeer, RP Pandey, B Rehman, T Safdar… - Journal of Water …, 2022 - Elsevier
Artificial intelligence (AI) is an emerging powerful novel technology that can model real-time
problems involving numerous intricacies. The modeling capabilities of AI techniques are …

Potential for artificial intelligence (AI) and machine learning (ML) applications in biodiversity conservation, managing forests, and related services in India

KN Shivaprakash, N Swami, S Mysorekar, R Arora… - Sustainability, 2022 - mdpi.com
The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction

N Baig, J Usman, SI Abba, M Benaafi… - Journal of Cleaner …, 2023 - Elsevier
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …