A PM2.5 Concentration Prediction in High-Cost and Low-Cost Wireless Sensor Networks Using Neural Networks-Reference-Cited by-同舟云学术

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A PM2.5 Concentration Prediction in High-Cost and Low-Cost Wireless Sensor Networks Using Neural Networks

Published:2023-10-25 Issue: Volume: Page:
ISSN:
Container-title:2023 16th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS)
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Author:

Marković Marko Ž.¹,Nešković Đorđe A.²,Kašca Lara A.³,Marković Goran B.³,Drajić Dejan D.⁴

Affiliation:

1. University of Belgrade,the School of Electrical Engineering,Belgrade,Serbia,11120

2. Vlatacom Institute,Belgrade,Serbia,11070

3. University of Belgrade,School of Electrical Engineering,Belgrade,Serbia,11120

4. University of Belgrade,School of Electrical Engineering,Belgrade,11200

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10315951/10315716/10316136.pdf?arnumber=10316136

Reference25 articles.

1. An improved deep learning model for predicting daily PM2.5 concentration

2. Application of XGBoost algorithm in hourly PM2.5 concentration prediction;pan;IOP Conf Ser Earth Environ Sci,2017

3. A deep learning model for air quality prediction in smart cities;kök;2017 IEEE International Conference on Big Data,2017

4. Deep Spatial-Temporal Fusion Network for Fine-Grained Air Quality Prediction

5. Living Well with Pollution? The Impact of the Concentration of PM2.5 on the Quality of Life of Patients with Asthma;?cibor;Int J Environ Res Public Health,2019

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