Performance evaluation of a recurrent deep neural network optimized by swarm intelligent techniques to model particulate matter
Author:
Affiliation:
1. Facultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro, México
Publisher
Informa UK Limited
Subject
Management, Monitoring, Policy and Law,Waste Management and Disposal
Link
https://www.tandfonline.com/doi/pdf/10.1080/10962247.2022.2095057
Reference53 articles.
1. Evaluation of Key Parameters Using Deep Convolutional Neural Networks for Airborne Pollution (PM10) Prediction
2. Airborne particle pollution predictive model using Gated Recurrent Unit (GRU) deep neural networks
3. A stacked approach for chained equations multiple imputation incorporating the substantive model
4. Swarm Intelligence in Cellular Robotic Systems
5. Effects of PM10 and Weather on Respiratory and Cardiovascular Diseases in the Ciuc Basin (Romanian Carpathians)
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