Bidirectional convolutional LSTM for the prediction of nitrogen dioxide in the city of Madrid.

ABSTRACT: Nitrogen dioxide is one of the pollutants with the most significant health effects. Advanced information on its concentration in the air can help to monitor and control further consequences more effectively, while also making it easier to apply preventive and mitigating measures. Machine learning technologies with available methods and capabilities, combined with the geospatial dimension, can perform predictive analyses with higher accuracy and, as a result, can serve as a supportive tool for productive management. One of the most advanced machine learning algorithms, Bidirectional convolutional LSTM, is being used in ongoing work to predict the concentration of nitrogen dioxide. The model has been validated to perform more accurate spatiotemporal analysis based on the integration of tempo

SUBMITTER: Iskandaryan D 

PROVIDER: S-EPMC9159618 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature