Cargando…
Forecasting Hazard Level of Air Pollutants Using LSTM’s
The South Asian countries have the most polluted cities in the world which has caused quite a concern in the recent years due to the detrimental effect it had on economy and on health of humans and crops. PM 2.5 in particular has been linked to cardiovascular diseases, pulmonary diseases, increased...
Autores principales: | Gul, Saba, Khan, Gul Muhammad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7256580/ http://dx.doi.org/10.1007/978-3-030-49186-4_13 |
Ejemplares similares
-
Short-term solar energy forecasting: Integrated computational intelligence of LSTMs and GRU
por: Zameer, Aneela, et al.
Publicado: (2023) -
Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO(2) (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain)
por: González-Enrique, Javier, et al.
Publicado: (2021) -
Child-Sum EATree-LSTMs: enhanced attentive Child-Sum Tree-LSTMs for biomedical event extraction
por: Wang, Lei, et al.
Publicado: (2023) -
Improving Road Traffic Forecasting Using Air Pollution and Atmospheric Data: Experiments Based on LSTM Recurrent Neural Networks
por: Awan, Faraz Malik, et al.
Publicado: (2020) -
Anomaly Detection Using an Ensemble of Multi-Point LSTMs
por: Lee, Geonseok, et al.
Publicado: (2023)