[HTML][HTML] Asynchronous federated learning on heterogeneous devices: A survey
Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …
global model is generated on the centralized aggregation server based on the parameters of …
Monash time series forecasting archive
Many businesses and industries nowadays rely on large quantities of time series data
making time series forecasting an important research area. Global forecasting models that …
making time series forecasting an important research area. Global forecasting models that …
The proper care and feeding of CAMELS: How limited training data affects streamflow prediction
Accurate streamflow prediction largely relies on historical meteorological records and
streamflow measurements. For many regions, however, such data are only scarcely …
streamflow measurements. For many regions, however, such data are only scarcely …
Semi-supervised air quality forecasting via self-supervised hierarchical graph neural network
Predicting air quality in fine spatiotemporal granularity is of great importance for air pollution
control and urban sustainability. However, existing studies are either focused on predicting …
control and urban sustainability. However, existing studies are either focused on predicting …
Joint air quality and weather prediction based on multi-adversarial spatiotemporal networks
Accurate and timely air quality and weather predictions are of great importance to urban
governance and human livelihood. Though many efforts have been made for air quality or …
governance and human livelihood. Though many efforts have been made for air quality or …
Modeling inter-station relationships with attentive temporal graph convolutional network for air quality prediction
Air pollution is an important environmental issue of increasing concern, which impacts
human health. Accurate air quality prediction is crucial for avoiding people suffering from …
human health. Accurate air quality prediction is crucial for avoiding people suffering from …
An IoT enabled system for enhanced air quality monitoring and prediction on the edge
Air pollution is a major issue resulting from the excessive use of conventional energy
sources in developing countries and worldwide. Particulate Matter less than 2.5 µm in …
sources in developing countries and worldwide. Particulate Matter less than 2.5 µm in …
Deep-AIR: A hybrid CNN-LSTM framework for fine-grained air pollution estimation and forecast in metropolitan cities
Air pollution presents a serious health challenge in urban metropolises. While accurately
monitoring and forecasting air pollution are highly crucial, existing data-driven models have …
monitoring and forecasting air pollution are highly crucial, existing data-driven models have …
Kill two birds with one stone: A multi-view multi-adversarial learning approach for joint air quality and weather prediction
Accurate and timely air quality and weather predictions are of great importance to urban
governance and human livelihood. Though many efforts have been made for air quality or …
governance and human livelihood. Though many efforts have been made for air quality or …
Effective PM2. 5 concentration forecasting based on multiple spatial–temporal GNN for areas without monitoring stations
IF Su, YC Chung, C Lee, PM Huang - Expert Systems with Applications, 2023 - Elsevier
With rapid industrial developments, air pollution has become a hot issue globally. Accurate
prediction of PM2. 5 (a category of particulate pollutant with a diameter of less than 2. 5 μ m) …
prediction of PM2. 5 (a category of particulate pollutant with a diameter of less than 2. 5 μ m) …