Machine Learning-Based Estimation of PM<sub>2.5</sub> Concentration Using Ground Surface DoFP Polarimeters-Reference-Cited by-同舟云学术

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Machine Learning-Based Estimation of PM_2.5 Concentration Using Ground Surface DoFP Polarimeters

Published:2022 Issue: Volume:10 Page:23489-23496
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Takruri Maen¹^ORCID,Abubakar Abubakar²^ORCID,Jallad Abdul-Halim³^ORCID,Altawil Basel⁴,Marpu Prashanth R.⁵,Bermak Amine²^ORCID

Affiliation:

1. Department of Electrical, Electronics, and Communications Engineering, American University of Ras Al Khaimah, Ras Al-Khaimah, United Arab Emirates

2. Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

3. Department of Electrical Engineering, United Arab Emirates University, Al Ain, United Arab Emirates

4. Yahsat Space Laboratory, Khalifa University (KU), Abu Dhabi, United Arab Emirates

5. Group 42, Abu Dhabi, United Arab Emirates

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09714356.pdf?arnumber=9714356

Reference52 articles.

1. Support vector machine with adaptive parameters in financial time series forecasting

2. Department of defense enhanced particulate matter surveillance program (EPMSP);engelbrecht,2008

3. Particulate Matter Pollution in the United Arab Emirates: Elemental Analysis and Phase Identification of Fine Particulate Pollutants

4. Analysis of fine-mode aerosol retrieval capabilities by different passive remote sensing instrument designs

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. State-of-art in modelling particulate matter (PM) concentration: a scoping review of aims and methods;Environment, Development and Sustainability;2024-04-02

2. Fine-Tuning of Predictive Models CNN-LSTM and CONV-LSTM for Nowcasting PM_2.5 Level;IEEE Access;2024

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