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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:

Selection of key features for PM2.5 prediction using a wavelet model and RBF-LSTM
Yi‐Chung Chen, Dong-Chi Li
Applied Intelligence (2020) Vol. 51, Iss. 4, pp. 2534-2555
Closed Access | Times Cited: 52

Showing 26-50 of 52 citing articles:

Understanding the Disparities of PM2.5 Air Pollution in Urban Areas via Deep Support Vector Regression
Yuling Xia, Teague McCracken, Tong Liu, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 19, pp. 8404-8416
Closed Access | Times Cited: 1
An adaptive spatio-temporal neural network for PM2.5 concentration forecasting
Xiaoxia Zhang, Qixiong Li, Dong Liang
Artificial Intelligence Review (2023) Vol. 56, Iss. 12, pp. 14483-14510
Closed Access | Times Cited: 4
Unveiling the Transparency of Prediction Models for Spatial PM2.5 over Singapore: Comparison of Different Machine Learning Approaches with eXplainable Artificial Intelligence
S. S. Sunder, Vinay Anand Tikkiwal, Arun Kumar, et al.
AI (2023) Vol. 4, Iss. 4, pp. 787-811
Open Access | Times Cited: 3
Deep learning/Kalman filter-based underwater localization in VLC systems
Wessam M. Salama, Moustafa H. Aly, Eman S. Amer
Optical and Quantum Electronics (2023) Vol. 55, Iss. 2
Open Access | Times Cited: 2
Enhanced Stacking Ensemble Model in Predictive Analytics of Environmental Sensor Data
J. Angelin Jebamalar, T. Kamalakannan
(2021), pp. 482-486
Closed Access | Times Cited: 5
Ensembling-mRBF-LSTM Framework for Prediction of Abnormal Traffic Flows
Yi‐Chung Chen, Shaochen Liu, Bo-Xiang Chen, et al.
(2020), pp. 206-213
Closed Access | Times Cited: 4
Traffic Flow Prediction and Analysis in Smart Cities Based on the WND-LSTM Model
SuYuan Ma, Mingye Zhao
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-9
Open Access | Times Cited: 3
Identifying key grid cells for crowd flow predictions based on CNN-based models with the Grad-CAM kit
Sheng-Min Chiu, Yow-Shin Liou, Yi‐Chung Chen, et al.
Applied Intelligence (2022) Vol. 53, Iss. 11, pp. 13323-13351
Closed Access | Times Cited: 3
Multi-classification Prediction of PM2.5 Concentration Based on Improved Adaptive Boosting Rotation Forest
Tan Deng, Yao Jia, Ni Liu, et al.
Journal of environmental chemical engineering (2024) Vol. 12, Iss. 6, pp. 114658-114658
Closed Access
Enhancing Environmental Policy Decisions in Korea and Japan Through AI-Driven Air Pollution Forecast
Yushin Kim, J S Kim, Sunghyun Cho, et al.
Sustainability (2024) Vol. 16, Iss. 23, pp. 10436-10436
Open Access
Enhancing Air Quality Prediction with an Adaptive PSO-Optimized CNN-Bi-LSTM Model
Xuguang Zhu, F.C. Zou, Shanghai Li
Applied Sciences (2024) Vol. 14, Iss. 13, pp. 5787-5787
Open Access
Hybrid Extreme Learning for Reliable Short-Term Traffic Flow Forecasting
Hsingyu Chen, Zhizhe Lin, Y. H. Yao, et al.
Mathematics (2024) Vol. 12, Iss. 20, pp. 3303-3303
Open Access
From Data to Diagnosis: Machine Learning Revolutionizes Epidemiological Predictions
Abdul Aziz Abdul Rahman, Gowri Rajasekaran, R. Rathipriya, et al.
Information (2024) Vol. 15, Iss. 11, pp. 719-719
Open Access
Establishing Lightweight and Robust Prediction Models for Solar Power Forecasting Using Numerical–Categorical Radial Basis Function Deep Neural Networks
Chee-Hoe Loh, Yi‐Chung Chen, Chwen‐Tzeng Su, et al.
Applied Sciences (2024) Vol. 14, Iss. 22, pp. 10625-10625
Open Access
Spatiotemporal distribution prediction for PM2.5 based on STXGBoost model and high-density monitoring sensors in Zhengzhou High Tech Zone, China
Shiqi Zhao, Hong Lin, Hongjun Wang, et al.
Journal of Environmental Management (2024) Vol. 373, pp. 123682-123682
Closed Access
Temporal-causal modeling of air pollution in the city of Plovdiv, Bulgaria: a case study
Atanas Ivanov, Snezhana Gocheva-Ilieva, Maya Stoimenova-Minova
Journal of Physics Conference Series (2023) Vol. 2675, Iss. 1, pp. 012002-012002
Open Access | Times Cited: 1
An adaptive spatio-temporal neural network for PM2.5 concentration forecasting
Xiaoxia Zhang, Qixiong Li, Dong Liang
Research Square (Research Square) (2023)
Closed Access | Times Cited: 1
A Hybrid Deep Learning Model Based on LSTM for Long-term PM2.5 Prediction
Yibin Chen, Mingyan Wu, Ruiping Tang, et al.
(2021) Vol. 8, pp. 55-60
Closed Access | Times Cited: 3
Towards optimal ATM cash replenishment using time series analysis
Muhammad Rafi, Mohammad Taha Wahab, Muhammad Bilal Khan, et al.
Journal of Intelligent & Fuzzy Systems (2021) Vol. 41, Iss. 6, pp. 5915-5927
Closed Access | Times Cited: 2
For the aged: A novel PM2.5 concentration forecasting method based on spatial-temporal graph ordinary differential equation networks in home-based care parks
Qingtian Zeng, Chao Wang, Geng Chen, et al.
Frontiers in Environmental Science (2022) Vol. 10
Open Access | Times Cited: 1
Good environmental governance: Predicting PM2.5 by using Spatiotemporal Matrix Factorization generative adversarial network
An Zhang, Sheng Chen, Fen Zhao, et al.
Frontiers in Environmental Science (2022) Vol. 10
Open Access | Times Cited: 1
Air Pollution Particulate Matter (PM2.5) Forecasting using Long Short Term Memory Model
Angga Vidianto, Achmad Rero Sindunata, Novanto Yudistira
(2021) Vol. 51, pp. 139-145
Closed Access | Times Cited: 1
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
Ensemble Learning with Hybrid Modelling for Multivariate AQI, PM2.5, and PM10 Forecasting in Mumbai
Anurag Singh, Pratham Soni, Deepa Krishnan, et al.
(2023), pp. 1-7
Closed Access
SAVE‐AS: Accelerating convergence in network traffic prediction through adaptive optimized variational mode decomposition and an integrated extreme learning machine
Jinmei Shi, Yu‐Beng Leau, Kun Li
International Journal of Communication Systems (2022) Vol. 35, Iss. 10
Closed Access

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