Article Versions Notes

González-Enrique J, Ruiz-Aguilar JJ, Moscoso-López JA, Urda D, Deka L, Turias IJ. Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO₂ (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain). Sensors. 2021; 21(5):1770. https://doi.org/10.3390/s21051770

González-Enrique, Javier, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso-López, Daniel Urda, Lipika Deka, and Ignacio J. Turias. 2021. "Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO₂ (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain)" Sensors 21, no. 5: 1770. https://doi.org/10.3390/s21051770

González-Enrique, J., Ruiz-Aguilar, J. J., Moscoso-López, J. A., Urda, D., Deka, L., & Turias, I. J. (2021). Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO₂ (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain). Sensors, 21(5), 1770. https://doi.org/10.3390/s21051770