Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Statistical PM2.5 Prediction in an Urban Area Using Vertical Meteorological Factors
Jutapas Saiohai, Surat Bualert, Thunyapat Thongyen, et al.
Atmosphere (2023) Vol. 14, Iss. 3, pp. 589-589
Open Access | Times Cited: 16

Showing 16 citing articles:

Multi-factor PM2.5 concentration optimization prediction model based on decomposition and integration
Hong Yang, Wenqian Wang, Guohui Li
Urban Climate (2024) Vol. 55, pp. 101916-101916
Closed Access | Times Cited: 12
Trend-attribute forecasting of hourly PM2.5 trends in fifteen cities of Central England applying optimized machine learning feature selection
David A. Wood
Journal of Environmental Management (2024) Vol. 356, pp. 120561-120561
Closed Access | Times Cited: 7
First temporal distribution model of ambient air pollutants (PM2.5, PM10, and O3) in Yangon City, Myanmar during 2019–2021
Tin Saw Pyae, Kraiwuth Kallawicha
Environmental Pollution (2024) Vol. 347, pp. 123718-123718
Closed Access | Times Cited: 5
Application of machine learning models for PM2.5 prediction in bengaluru using precursor air pollutants and meteorological data
Gourav Suthar, Saurabh Singh
Theoretical and Applied Climatology (2025) Vol. 156, Iss. 3
Closed Access
Prediction of Particulate Matter PM2.5 Using Bidirectional Gated Recurrent Unit with Feature Selection

Global NEST Journal (2024)
Open Access | Times Cited: 1
Analyzing meteorological factors for forecasting PM10 and PM2.5 levels: a comparison between MLR and MLP models
Nastaran Talepour, Yaser Tahmasebi Birgani, Frank J. Kelly, et al.
Earth Science Informatics (2024)
Closed Access | Times Cited: 1
TimesNet-PM2.5: Interpretable TimesNet for Disentangling Intraperiod and Interperiod Variations in PM2.5 Prediction
Yiming Huang, Ziyu Zhou, Zihao Wang, et al.
Atmosphere (2023) Vol. 14, Iss. 11, pp. 1604-1604
Open Access | Times Cited: 2
Prediction of daily fine particulate matter (PM2.5) concentration in Aksaray, Turkey: Temporal variation, meteorological dependence, and employing artificial neural network
Ebru Koçak
Environmental Progress & Sustainable Energy (2024) Vol. 43, Iss. 2
Closed Access
Predicting PM2.5 concentration with enhanced state–trend awareness and uncertainty analysis using bagging and LSTM neural networks
Bian Chao, Guangqiu Huang
Journal of Environmental Quality (2024) Vol. 53, Iss. 4, pp. 441-455
Closed Access
Future Air Quality Prediction Using Long Short-Term Memory Based on Hyper Heuristic Multi-Chain Model
Kalyan Chatterjee, Samla Suraj Kumar, Ramagiri Praveen Kumar, et al.
IEEE Access (2024) Vol. 12, pp. 123678-123693
Open Access
Characterizing PM2.5 Pollution in Urban Jakarta: Insights from Morphology, Elemental Composition, and Concentration Analysis
Fatimah Dinan Qonitan, Nadhine Wahyutami Kuncoro, Ari Rahman, et al.
Springer proceedings in physics (2024), pp. 87-99
Closed Access
PM2.5 concentration prediction algorithm integrating traffic congestion index
Yong Fang, Shicheng Zhang, Keyong Yu, et al.
Journal of Environmental Sciences (2024)
Closed Access
An Ensemble Deep Learning Algorithm to Predict PM2.5 Concentration Levels in Bengaluru’s Atmosphere
Tushar Patil, Lichingngamba Tensubam, Nivedan Yakolli, et al.
Communications in computer and information science (2023), pp. 316-327
Closed Access
H2MaM: Future Air Quality Prediction using LSTM-based Hyper Heuristic Multi-Chain Model
Sweta Dey, Kalyan Chatterjee, Anjan Bandyopadhyay, et al.
(2023)
Open Access
H2MaM: Future Air Quality Prediction using LSTM-based Hyper Heuristic Multi-Chain Model
Sweta Dey, Kalyan Chatterjee, Anjan Bandyopadhyay, et al.
(2023)
Open Access
Artificial Neural Network Based Prediction of PM2.5 Mass Concentration
Carolina Dwi Sundari, A.N. A.R. Putri, I.W. Kinanti, et al.
(2023), pp. 1-6
Closed Access
Page 1

Scroll to top