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:

Air quality forecasting with hybrid LSTM and extended stationary wavelet transform
Yongkang Zeng, Jingjing Chen, Ning Jin, et al.
Building and Environment (2022) Vol. 213, pp. 108822-108822
Open Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

Deep learning for air pollutant concentration prediction: A review
Bo Zhang, Yi Rong, Ruihan Yong, et al.
Atmospheric Environment (2022) Vol. 290, pp. 119347-119347
Closed Access | Times Cited: 125
LSTM-Autoencoder-Based Anomaly Detection for Indoor Air Quality Time-Series Data
Yuanyuan Wei, Julian Jang‐Jaccard, Wen Xu, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 4, pp. 3787-3800
Open Access | Times Cited: 104
Artificial Intelligence Technologies for Forecasting Air Pollution and Human Health: A Narrative Review
S. Shankar, Naveenkumar Raju, Abbas Ganesan, et al.
Sustainability (2022) Vol. 14, Iss. 16, pp. 9951-9951
Open Access | Times Cited: 84
Artificial neural network an innovative approach in air pollutant prediction for environmental applications: A review
Vibha Yadav, Amit Kumar Yadav, Vedant Singh, et al.
Results in Engineering (2024) Vol. 22, pp. 102305-102305
Open Access | Times Cited: 17
A multi-scale evolutionary deep learning model based on CEEMDAN, improved whale optimization algorithm, regularized extreme learning machine and LSTM for AQI prediction
Chunlei Ji, Chu Zhang, Lei Hua, et al.
Environmental Research (2022) Vol. 215, pp. 114228-114228
Closed Access | Times Cited: 59
Machine learning applications on air temperature prediction in the urban canopy layer: A critical review of 2011–2022
Han Wang, Jiachuan Yang, Guangzhao Chen, et al.
Urban Climate (2023) Vol. 49, pp. 101499-101499
Closed Access | Times Cited: 30
Forecasting of fine particulate matter based on LSTM and optimization algorithm
Nur’atiah Zaini, Ali Najah Ahmed, Lee Woen Ean, et al.
Journal of Cleaner Production (2023) Vol. 427, pp. 139233-139233
Closed Access | Times Cited: 24
An innovative provincial CO2 emission quota allocation scheme for Chinese low-carbon transition
Fan Yang, Hyoung Seok Lee
Technological Forecasting and Social Change (2022) Vol. 182, pp. 121823-121823
Closed Access | Times Cited: 30
A Solar Irradiance Forecasting Framework Based on the CEE-WGAN-LSTM Model
Qianqian Li, Dongping Zhang, Ke Yan
Sensors (2023) Vol. 23, Iss. 5, pp. 2799-2799
Open Access | Times Cited: 17
A unified deep learning framework for water quality prediction based on time-frequency feature extraction and data feature enhancement
Rui Xu, Shengri Hu, Hang Wan, et al.
Journal of Environmental Management (2023) Vol. 351, pp. 119894-119894
Closed Access | Times Cited: 17
Robust multi-modal pedestrian detection using deep convolutional neural network with ensemble learning model
Deepak Kumar Jain, Xudong Zhao, Salvador García, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123527-123527
Closed Access | Times Cited: 5
PM2.5 concentration forecasting: Development of integrated multivariate variational mode decomposition with kernel Ridge regression and weighted mean of vectors optimization
Tao Hai, Iman Ahmadianfar, Leonardo Goliatt, et al.
Atmospheric Pollution Research (2024) Vol. 15, Iss. 6, pp. 102125-102125
Closed Access | Times Cited: 5
Comprehensive analysis of various imputation and forecasting models for predicting PM2.5 pollutant in Delhi
Hemanth Karnati, A. K. Soma, A K M Mubashwir Alam, et al.
Neural Computing and Applications (2025)
Open Access
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: 22
Measuring and Modelling the Concentration of Vehicle-Related PM2.5 and PM10 Emissions Based on Neural Networks
Vladimir Shepelev, Aleksandr Glushkov, Ivan Slobodin, et al.
Mathematics (2023) Vol. 11, Iss. 5, pp. 1144-1144
Open Access | Times Cited: 12
Short-Term PM2.5 Prediction Based on Multi-Modal Meteorological Data for Consumer-Grade Meteorological Electronic Systems
Lina Wang, Xiaochen Jin, Zengyang Huang, et al.
IEEE Transactions on Consumer Electronics (2024) Vol. 70, Iss. 1, pp. 3464-3474
Closed Access | Times Cited: 4
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
Long Short‐Term Memory Wavelet Neural Network for Renewable Energy Generation Forecasting
Eliana Vivas, Héctor Allende‐Cid, Lelys Bravo de Guenni, et al.
International Journal of Intelligent Systems (2025) Vol. 2025, Iss. 1
Open Access
Phy-APMR: A physics-informed air pollution map reconstruction approach with mobile crowd-sensing for fine-grained measurement
Rongye Shi, Ji Luo, Nan Zhou, et al.
Building and Environment (2025), pp. 112634-112634
Closed Access
Financial Time Series Forecasting: A Comprehensive Review of Signal Processing and Optimization-Driven Intelligent Models
Matoori Praveen, Satish Dekka, Sai Dai, et al.
Computational Economics (2025)
Closed Access
Multivariate Air Quality Forecasting with Residual Nested LSTM Neural Network Based on DSWT
Weijian Li, Yiwen Zhang, Yaoyao Liu
Sustainability (2025) Vol. 17, Iss. 5, pp. 2244-2244
Open Access
Integrating Experimental Analysis and Machine Learning for Enhancing Energy Efficiency and Indoor Air Quality in Educational Buildings
Seyed Hamed Godasiaei, Obuks Ejohwomu, Hua Zhong, et al.
Building and Environment (2025), pp. 112874-112874
Closed Access
A Hybrid Air Quality Prediction Model Based on Empirical Mode Decomposition
Yuxuan Cao, D. Zhang, Shaoqi Ding, et al.
Tsinghua Science & Technology (2023) Vol. 29, Iss. 1, pp. 99-111
Open Access | Times Cited: 9
A Novel Hybrid Prediction Model of Air Quality Index Based on Variational Modal Decomposition and CEEMDAN-SE-GRU
Chaoli Tang, Ziyu Wang, Yuanyuan Wei, et al.
Process Safety and Environmental Protection (2024) Vol. 191, pp. 2572-2588
Closed Access | Times Cited: 3
Short-Term Photovoltaic Power Forecasting Based on Historical Information and Deep Learning Methods
Xianchao Guo, Yuchang Mo, Ke Yan
Sensors (2022) Vol. 22, Iss. 24, pp. 9630-9630
Open Access | Times Cited: 14
Page 1 - Next Page

Scroll to top