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OpenAlex Citation Counts

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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:

A Lag-FLSTM deep learning network based on Bayesian Optimization for multi-sequential-variant PM2.5 prediction
Jun Ma, Yuexiong Ding, Jack C.P. Cheng, et al.
Sustainable Cities and Society (2020) Vol. 60, pp. 102237-102237
Closed Access | Times Cited: 97

Showing 26-50 of 97 citing articles:

A hybrid carbon price prediction model based-combinational estimation strategies of quantile regression and long short-term memory
Nijun Jiang, Xiaobing Yu, Manawwer Alam
Journal of Cleaner Production (2023) Vol. 429, pp. 139508-139508
Closed Access | Times Cited: 17
A novel hourly PM2.5 concentration prediction model based on feature selection, training set screening, and mode decomposition-reorganization
Wei Sun, Zhiwei Xu
Sustainable Cities and Society (2021) Vol. 75, pp. 103348-103348
Closed Access | Times Cited: 39
Forecasting hourly PM2.5 based on deep temporal convolutional neural network and decomposition method
Fuxin Jiang, Chengyuan Zhang, Shaolong Sun, et al.
Applied Soft Computing (2021) Vol. 113, pp. 107988-107988
Closed Access | Times Cited: 39
Forecasting PM2.5 levels in Santiago de Chile using deep learning neural networks
Camilo Menares, Patricio Pérez, Santiago Parraguez, et al.
Urban Climate (2021) Vol. 38, pp. 100906-100906
Closed Access | Times Cited: 37
Methods used for handling and quantifying model uncertainty of artificial neural network models for air pollution forecasting
Sheen Mclean Cabaneros, Ben Richard Hughes
Environmental Modelling & Software (2022) Vol. 158, pp. 105529-105529
Open Access | Times Cited: 23
Hyperparameter Optimization of Bayesian Neural Network Using Bayesian Optimization and Intelligent Feature Engineering for Load Forecasting
M. Zulfiqar, Kelum A. A. Gamage, Muhammad Kamran, et al.
Sensors (2022) Vol. 22, Iss. 12, pp. 4446-4446
Open Access | Times Cited: 22
Physics-informed ensemble deep learning framework for improving state of charge estimation of lithium-ion batteries
Hanqing Yu, Zhengjie Zhang, Kaiyi Yang, et al.
Journal of Energy Storage (2023) Vol. 73, pp. 108915-108915
Closed Access | Times Cited: 15
Long-term PM2.5 concentrations forecasting using CEEMDAN and deep Transformer neural network
Qiaolin Zeng, Lihui Wang, Songyan Zhu, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 9, pp. 101839-101839
Closed Access | Times Cited: 14
Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data
S. Y. Zhu, Jiayi Tang, Xiaolu Zhou, et al.
Environmental Reviews (2023) Vol. 31, Iss. 4, pp. 605-631
Open Access | Times Cited: 13
Multi-level lag scheme significantly improves training efficiency in deep learning: a case study in air quality alert service over sub-tropical area
Benedito Chi Man Tam, Su-Kit Tang, Alberto Cardoso
Journal Of Big Data (2025) Vol. 12, Iss. 1
Open Access
Transfer learning–based energy consumption prediction for variable refrigerant flow system in buildings
Chanwoo Park, Icksung Kim, Woohyun Kim
Applied Thermal Engineering (2025) Vol. 267, pp. 125811-125811
Closed Access
Systems classification of air pollutants using Adam optimized CNN with XGBoost feature selection
Satya Prakash, K. Sangeetha
Analog Integrated Circuits and Signal Processing (2025) Vol. 122, Iss. 3
Closed Access
Deep Aggregation seq2seq Network With Time Feature Fusion for Air Pollutant Concentration Prediction in Smart Cities
Y Liu
Engineering Reports (2025) Vol. 7, Iss. 2
Open Access
A balanced social LSTM for PM2.5 concentration prediction based on local spatiotemporal correlation
Lukui Shi, Huizhen Zhang, Xia Xu, et al.
Chemosphere (2021) Vol. 291, pp. 133124-133124
Closed Access | Times Cited: 30
Including the feature of appropriate adjacent sites improves the PM2.5 concentration prediction with long short-term memory neural network model
Mengfan Teng, Siwei Li, Ge Song, et al.
Sustainable Cities and Society (2021) Vol. 76, pp. 103427-103427
Open Access | Times Cited: 28
New PM2.5 forecasting system based on combined neural network and an improved multi-objective optimization algorithm: Taking the economic belt surrounding the Bohai Sea as an example
Zhirui Tian, Gai Mei
Journal of Cleaner Production (2022) Vol. 375, pp. 134048-134048
Closed Access | Times Cited: 20
Exploiting PSO-SVM and sample entropy in BEMD for the prediction of interval-valued time series and its application to daily PM2.5 concentration forecasting
Liyuan Jiang, Zhifu Tao, Jiaming Zhu, et al.
Applied Intelligence (2022) Vol. 53, Iss. 7, pp. 7599-7613
Closed Access | Times Cited: 19
Comparative Analysis of Deep Learning and Statistical Models for Air Pollutants Prediction in Urban Areas
Fareena Naz, Conor McCann, Muhammad Fahim, et al.
IEEE Access (2023) Vol. 11, pp. 64016-64025
Open Access | Times Cited: 11
A comprehensive study of macro factors related to traffic fatality rates by XGBoost-based model and GIS techniques
Feifeng Jiang, Jun Ma
Accident Analysis & Prevention (2021) Vol. 163, pp. 106431-106431
Closed Access | Times Cited: 25
A hybrid integrated deep learning model for predicting various air pollutants
Wenjing Mao, Limin Jiao, Weilin Wang, et al.
GIScience & Remote Sensing (2021) Vol. 58, Iss. 8, pp. 1395-1412
Open Access | Times Cited: 24
A long short-term memory-based hybrid model optimized using a genetic algorithm for particulate matter 2.5 prediction
Anıl Utku, Ümit Can, Mustafa Kamal, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 8, pp. 101836-101836
Closed Access | Times Cited: 9
Short-term prediction of PM2.5 concentration by hybrid neural network based on sequence decomposition
Xiaoxuan Wu, Jun Zhu, Qiang Wen
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0299603-e0299603
Open Access | Times Cited: 3
Auto imputation enabled deep Temporal Convolutional Network (TCN) model for pm2.5 forecasting
K. Krishna Rani Samal
ICST Transactions on Scalable Information Systems (2024) Vol. 11
Open Access | Times Cited: 3
Hazard Susceptibility Mapping with Machine and Deep Learning: A Literature Review
Angelly de Jesus Pugliese Viloria, A. Folini, Daniela Carrión, et al.
Remote Sensing (2024) Vol. 16, Iss. 18, pp. 3374-3374
Open Access | Times Cited: 3
A combined prediction system for PM2.5 concentration integrating spatio-temporal correlation extracting, multi-objective optimization weighting and non-parametric estimation
Jianzhou Wang, Yuansheng Qian, Yuyang Gao, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 10, pp. 101880-101880
Closed Access | Times Cited: 8

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