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[HTML][HTML] Roles of artificial intelligence and machine learning in enhancing construction processes and sustainable communities
Machine Learning (ML), a subset of Artificial Intelligence (AI), is gaining popularity in the
architectural, engineering, and construction (AEC) sector. This systematic study aims to …
architectural, engineering, and construction (AEC) sector. This systematic study aims to …
Applications and prospects of artificial intelligence in covert satellite communication: a review
Satellite communication has the characteristics of wide coverage and large communication
capacity, and is not easily affected by land disasters. It is quite suitable as a supplement to …
capacity, and is not easily affected by land disasters. It is quite suitable as a supplement to …
Predicting of Daily PM2.5 Concentration Employing Wavelet Artificial Neural Networks Based on Meteorological Elements in Shanghai, China
Q Guo, Z He, Z Wang - Toxics, 2023 - mdpi.com
Anthropogenic sources of fine particulate matter (PM2. 5) threaten ecosystem security,
human health and sustainable development. The accuracy prediction of daily PM2. 5 …
human health and sustainable development. The accuracy prediction of daily PM2. 5 …
Causal intervention for human trajectory prediction with cross attention mechanism
Human trajectory Prediction (HTP) in complex social environments plays a crucial and
fundamental role in artificial intelligence systems. Conventional methods make use of both …
fundamental role in artificial intelligence systems. Conventional methods make use of both …
Low‐cost air quality monitoring networks for long‐term field campaigns: A review
The application of low‐cost air quality monitoring networks has substantially grown over the
last few years, following the technological advances in the production of cheap and portable …
last few years, following the technological advances in the production of cheap and portable …
[HTML][HTML] Systematic Review of Machine Learning and Deep Learning Techniques for Spatiotemporal Air Quality Prediction
Background: Although computational models are advancing air quality prediction, achieving
the desired performance or accuracy of prediction remains a gap, which impacts the …
the desired performance or accuracy of prediction remains a gap, which impacts the …
Data-driven priors for robust PSSE via Gauss-Newton unrolled neural networks
Renewable energy sources, elastic loads, and purposeful manipulation of meter readings
challenge the monitoring and control of today's power systems (PS). In this context, fast and …
challenge the monitoring and control of today's power systems (PS). In this context, fast and …
A multi-task stations cooperative air quality prediction system for sustainable development
B Li, P Wang - Humanities and Social Sciences Communications, 2024 - nature.com
In recent years, A series of environmental problems caused by air pollution have attracted
widespread attention. Air quality forecasting has become an indispensable part of people's …
widespread attention. Air quality forecasting has become an indispensable part of people's …
Air pollution prediction system using XRSTH-LSTM algorithm
Globally, there are significant worries about the rise in air pollution (AP) from substances that
are harmful to human health, different living forms, and unfavorable environmental …
are harmful to human health, different living forms, and unfavorable environmental …
Efficient inference of large-scale air quality using a lightweight ensemble predictor
Accurate and efficient air quality prediction is crucial for public health protection and
environmental sustainability. While numerous grid-based and graph-based prediction …
environmental sustainability. While numerous grid-based and graph-based prediction …