Research on the factors influencing nanofiltration membrane fouling and the prediction of membrane fouling

W Zheng, Y Chen, X Xu, X Peng, Y Niu, P Xu… - Journal of Water Process …, 2024 - Elsevier
The issue of membrane fouling poses a significant challenge to the extensive adoption of
nanofiltration membrane technology in public water supply systems. The occurrence of …

A state-of-the-art review of long short-term memory models with applications in hydrology and water resources

Z Feng, J Zhang, W Niu - Applied Soft Computing, 2024 - Elsevier
Abstract Long Short-Term Memory (LSTM) has recently emerged as a crucial tool for
scientific research in hydrology and water resources. Despite its widespread use, a …

Anzali wetland crisis: unraveling the decline of Iran's ecological gem

M Mahdian, R Noori, MM Salamattalab… - Journal of …, 2024 - Wiley Online Library
The wetland loss rate in Iran is faster than the global average. Comprehending the
shrinkage rate in Iranian wetlands and identifying the underlying drivers of these changes is …

Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches

A Aldrees, M Khan, ATB Taha, M Ali - Journal of Water Process …, 2024 - Elsevier
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …

Modelling impacts of climate change and anthropogenic activities on inflows and sediment loads of wetlands: Case study of the Anzali wetland

M Mahdian, M Hosseinzadeh, SM Siadatmousavi… - Scientific Reports, 2023 - nature.com
Understanding the effects of climate change and anthropogenic activities on the
hydrogeomorpholgical parameters in wetlands ecosystems is vital for designing effective …

[HTML][HTML] Marine waters assessment using improved water quality model incorporating machine learning approaches

MG Uddin, A Rahman, S Nash, MTM Diganta… - Journal of …, 2023 - Elsevier
In marine ecosystems, both living and non-living organisms depend on “good” water quality.
It depends on a number of factors, and one of the most important is the quality of the water …

Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion

H Gholami, A Mohammadifar, S Golzari, Y Song… - Science of the Total …, 2023 - Elsevier
Gully erosion possess a serious hazard to critical resources such as soil, water, and
vegetation cover within watersheds. Therefore, spatial maps of gully erosion hazards can be …

Efficient data-driven machine learning models for scour depth predictions at slo** sea defences

MA Habib, S Abolfathi, JJ O'Sullivan… - Frontiers in Built …, 2024 - frontiersin.org
Seawalls are critical defence infrastructures in coastal zones that protect hinterland areas
from storm surges, wave overtop** and soil erosion hazards. Scouring at the toe of sea …

Machine learning prediction of wave characteristics: Comparison between semi-empirical approaches and DT model

A Yeganeh-Bakhtiary, H EyvazOghli, N Shabakhty… - Ocean …, 2023 - Elsevier
Prediction of wave characteristics plays a crucial role in design and performance
assessment of various coastal projects. The computational complexity and time-consuming …

Revolutionizing biochar synthesis for enhanced heavy metal adsorption: Harnessing machine learning and Bayesian optimization

H Yang, X Liu, Y Liu, J Cui, Y **ao - Journal of Environmental Chemical …, 2023 - Elsevier
Biochar is widely recognized as an effective approach for mitigating heavy metal pollution.
However, the utilization of machine learning models to guide biochar preparation and …