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A New Regularized Spatiotemporal Attention-Based LSTM with Application to Nitrogen Oxides Emission Prediction
[Image: see text] The data collected from complex process industries are usually time series with considerable nonlinearities and dynamics, as well as excessive redundancy. Moreover, there are temporal and spatial correlations between input variables and key performance variables. These characterist...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Chemical Society
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099443/ https://www.ncbi.nlm.nih.gov/pubmed/37065070 http://dx.doi.org/10.1021/acsomega.2c08205 |