[HTML][HTML] A deep dive into membrane distillation literature with data analysis, bibliometric methods, and machine learning
Membrane distillation (MD) is a non-isothermal separation process applied mainly in
desalination for the treatment of saline aqueous solutions including brines for distilled water …
desalination for the treatment of saline aqueous solutions including brines for distilled water …
[HTML][HTML] Faradaic deionization technology: Insights from bibliometric, data mining and machine learning approaches
E Aytaç, A Fombona-Pascual, JJ Lado, EG Quismondo… - Desalination, 2023 - Elsevier
Faradaic deionization (FDI) is an emerging water treatment technology based on electrodes
able to remove ionic species from water by charge transfer reactions. It is a young and …
able to remove ionic species from water by charge transfer reactions. It is a young and …
A review of machine learning and deep learning for object detection, semantic segmentation, and human action recognition in machine and robotic vision
Machine vision, an interdisciplinary field that aims to replicate human visual perception in
computers, has experienced rapid progress and significant contributions. This paper traces …
computers, has experienced rapid progress and significant contributions. This paper traces …
Geospatial artificial intelligence (GeoAI) in the integrated hydrological and fluvial systems modeling: Review of current applications and trends
This paper reviews the current GeoAI and machine learning applications in hydrological and
hydraulic modeling, hydrological optimization problems, water quality modeling, and fluvial …
hydraulic modeling, hydrological optimization problems, water quality modeling, and fluvial …
[PDF][PDF] Evaluation of machine learning methods application in temperature prediction
Machine Learning (ML) techniques for time series prediction are becoming increasingly
accurate and helpful, particularly in considering climate change. As more methods are …
accurate and helpful, particularly in considering climate change. As more methods are …
Bibliometric and sentiment analysis with machine learning on the scientific contribution of Professor Srinivasa Sourirajan
Abstract Prof. Srinivasa Sourirajan is remembered by the desalination and membrane
community as the “Father of Reverse Osmosis”. He passed away at the age of 98 peacefully …
community as the “Father of Reverse Osmosis”. He passed away at the age of 98 peacefully …
Multiple spatio-temporal scale runoff forecasting and driving mechanism exploration by K-means optimized XGBoost and SHAP
S Wang, H Peng - Journal of Hydrology, 2024 - Elsevier
Hydrological simulations have seen extensive use of machine learning (ML) models.
However, the existing ML models face challenges in effectively handling temporal and …
However, the existing ML models face challenges in effectively handling temporal and …
Evaluation of social factors within the circular economy concept for European countries
The circular economy (CE) is a rapidly growing theme, particularly in the European Union
(EU), that encourages the responsible and circular use of resources in the field of …
(EU), that encourages the responsible and circular use of resources in the field of …
Exploring a multi-objective cluster-decomposition framework for optimizing flood control operation rules of cascade reservoirs in a river basin
Multi-objective flood control operation of cascade reservoirs is a vital issue in river basin
management. However, traditional multi-objective approaches commonly provide one …
management. However, traditional multi-objective approaches commonly provide one …
Review of machine learning techniques for power electronics control and optimization
M Bahrami, Z Khashroum - arXiv preprint arXiv:2310.04699, 2023 - arxiv.org
In the rapidly advancing landscape of contemporary technology, power electronics assume
a pivotal role across diverse applications, ranging from renewable energy systems to electric …
a pivotal role across diverse applications, ranging from renewable energy systems to electric …