Urban foundation models: A survey
Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models
Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
Dewp: Deep expansion learning for wind power forecasting
Wind is one kind of high-efficient, environmentally-friendly, and cost-effective energy source.
Wind power, as one of the largest renewable energy in the world, has been playing a more …
Wind power, as one of the largest renewable energy in the world, has been playing a more …
Air quality prediction with physics-informed dual neural odes in open systems
Air pollution significantly threatens human health and ecosystems, necessitating effective air
quality prediction to inform public policy. Traditional approaches are generally categorized …
quality prediction to inform public policy. Traditional approaches are generally categorized …
Diffusion-driven Incomplete Multimodal Learning for Air Quality Prediction
Predicting air quality using multimodal data is crucial to comprehensively capture the
diverse factors influencing atmospheric conditions. Therefore, this study introduces a …
diverse factors influencing atmospheric conditions. Therefore, this study introduces a …
Spatio-Temporal Field Neural Networks for Air Quality Inference
The air quality inference problem aims to utilize historical data from a limited number of
observation sites to infer the air quality index at an unknown location. Considering the …
observation sites to infer the air quality index at an unknown location. Considering the …
A Prompt-Guided Spatio-Temporal Transformer Model for National-Wide Nuclear Radiation Forecasting
Nuclear radiation (NR), which refers to the energy emitted from atomic nuclei during decay,
poses substantial risks to human health and environmental safety. Accurate forecasting of …
poses substantial risks to human health and environmental safety. Accurate forecasting of …
Spatio-Temporal Forecasting of PM2. 5 via Spatial-Diffusion guided Encoder-Decoder Architecture
M Pandey, V Jain, N Godhani, SN Tripathi… - arXiv preprint arXiv …, 2024 - arxiv.org
In many problem settings that require spatio-temporal forecasting, the values in the time-
series not only exhibit spatio-temporal correlations but are also influenced by spatial …
series not only exhibit spatio-temporal correlations but are also influenced by spatial …
LLMAir: Adaptive Reprogramming Large Language Model for Air Quality Prediction
Accurate and timely air quality prediction is crucial for cities and individuals to effectively
take necessary precautions against potential air pollution. Existing studies typically rely on …
take necessary precautions against potential air pollution. Existing studies typically rely on …
MTAGCN: Mixed Temporal Adaptive GCN for Air Pollution Prediction
Y Cheng, Z Wang - 2024 20th International Conference on …, 2024 - ieeexplore.ieee.org
As a crucial issue for the advancement of intelligent urban centers, the urgent resolution of
air pollution in urban areas is necessary. The essential task for accurate air pollution …
air pollution in urban areas is necessary. The essential task for accurate air pollution …