Hybrid model for air quality prediction based on LSTM with random search and Bayesian optimization techniques

Earth Science Informatics, Год журнала: 2024, Номер 18(1)

Опубликована: Дек. 12, 2024

Язык: Английский

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Fine particulate matter concentration prediction based on hybrid convolutional network with aggregated local and global spatiotemporal information: A case study in Beijing and Chongqing

Atmospheric Environment, Год журнала: 2024, Номер 333, С. 120647 - 120647

Опубликована: Июнь 12, 2024

Язык: Английский

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A Hybrid Model for Spatiotemporal Air Quality Prediction Based on Interpretable Neural Networks and a Graph Neural Network

Atmosphere, Год журнала: 2023, Номер 14(12), С. 1807 - 1807

Опубликована: Дек. 9, 2023

To effectively address air pollution and enhance quality, governments must be able to predict the quality index with high accuracy reliability. However, prediction is subject ambiguity instability because of atmosphere’s fluidity, making it challenging identify temporal spatial correlations using a single model. Therefore, new hybrid model proposed based on an interpretable neural network graph (INNGNN), which simulates dependence achieves accurate multi-step prediction. A time series first interpreted networks (INN) extract potentially important aspects that are easily overlooked in data; second, self-attention mechanism catches local global dependencies associations series. Lastly, city map created (GNN) determine relationships between cities order spatially dependent features. In experimental evaluation, results show INNGNN performs better than comparable algorithms. confirmed can capture quality.

Язык: Английский

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Empirical assessment of transformer-based neural network architecture in forecasting pollution trends

International Journal of Data Science and Analytics, Год журнала: 2023, Номер unknown

Опубликована: Июнь 30, 2023

Язык: Английский

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Citywide PM2.5 Concentration Prediction Using Deep Learning Model

Опубликована: Июнь 21, 2024

Язык: Английский

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Long-term urban air quality prediction with hierarchical attention loop network

Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 106010 - 106010

Опубликована: Ноя. 1, 2024

Язык: Английский

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