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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:

Estimation of municipal solid waste amount based on one-dimension convolutional neural network and long short-term memory with attention mechanism model: A case study of Shanghai
Kunsen Lin, Youcai Zhao, Lu Tian, et al.
The Science of The Total Environment (2021) Vol. 791, pp. 148088-148088
Closed Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

Analysis of input set characteristics and variances on k-fold cross validation for a Recurrent Neural Network model on waste disposal rate estimation
Lan Vu, Kelvin Tsun Wai Ng, Amy Richter, et al.
Journal of Environmental Management (2022) Vol. 311, pp. 114869-114869
Closed Access | Times Cited: 131
Toward smarter management and recovery of municipal solid waste: A critical review on deep learning approaches
Kunsen Lin, Youcai Zhao, Jia‐Hong Kuo, et al.
Journal of Cleaner Production (2022) Vol. 346, pp. 130943-130943
Closed Access | Times Cited: 104
Recent advances in applications of artificial intelligence in solid waste management: A review
Ihsanullah Ihsanullah, Gulzar Alam, Arshad Jamal, et al.
Chemosphere (2022) Vol. 309, pp. 136631-136631
Open Access | Times Cited: 80
Deep convolutional neural networks for construction and demolition waste classification: VGGNet structures, cyclical learning rate, and knowledge transfer
Kunsen Lin, Tao Zhou, Xiaofeng Gao, et al.
Journal of Environmental Management (2022) Vol. 318, pp. 115501-115501
Closed Access | Times Cited: 43
MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting
Kunsen Lin, Youcai Zhao, Lina Wang, et al.
Frontiers of Environmental Science & Engineering (2023) Vol. 17, Iss. 6
Open Access | Times Cited: 26
Enhancing door-to-door waste collection forecasting through ML
Luca Pasa, Giuseppe Angelini, Michele Ballarin, et al.
Waste Management (2025) Vol. 194, pp. 36-44
Open Access | Times Cited: 1
A systematic literature review on municipal solid waste management using machine learning and deep learning
Ishaan Dawar, Anurag K. Srivastava, Maanas Singal, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 6
Open Access | Times Cited: 1
Machine learning-assisted solid waste life-cycle management: Applications, constrains, and future opportunities
Qiuxia Zou, Huabo Duan, Zhirui Yang, et al.
Resources Conservation and Recycling (2025) Vol. 219, pp. 108320-108320
Closed Access | Times Cited: 1
City classification for municipal solid waste prediction in mainland China based on K-means clustering
Xingyu Du, Dongjie Niu, Yu Chen, et al.
Waste Management (2022) Vol. 144, pp. 445-453
Closed Access | Times Cited: 35
The Prediction of Carbon Emission Information in Yangtze River Economic Zone by Deep Learning
Huafang Huang, Xiaomao Wu, Cheng Xian-fu
Land (2021) Vol. 10, Iss. 12, pp. 1380-1380
Open Access | Times Cited: 41
Forecasting municipal solid waste in Lithuania by incorporating socioeconomic and geographical factors
Agnė Paulauskaitė-Tarasevičienė, Vidas Raudonis, Kristina Šutienė
Waste Management (2022) Vol. 140, pp. 31-39
Closed Access | Times Cited: 27
Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning
Sabbir Ahmed, Sameera Mubarak, Jia Tina Du, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 24, pp. 16798-16798
Open Access | Times Cited: 22
Combustion performance of fine screenings from municipal solid waste: Thermo-kinetic investigation and deep learning modeling via TG-FTIR
Lu Tian, Kunsen Lin, Youcai Zhao, et al.
Energy (2021) Vol. 243, pp. 122783-122783
Closed Access | Times Cited: 24
Modeling of municipal waste disposal behaviors related to meteorological seasons using recurrent neural network LSTM models
Kenneth K. Adusei, Kelvin Tsun Wai Ng, Nima Karimi, et al.
Ecological Informatics (2022) Vol. 72, pp. 101925-101925
Closed Access | Times Cited: 19
Hourly Heat Load Prediction for Residential Buildings Based on Multiple Combination Models: A Comparative Study
Wenhan An, Xiangyuan Zhu, Kaimin Yang, et al.
Buildings (2023) Vol. 13, Iss. 9, pp. 2340-2340
Open Access | Times Cited: 11
Investigation into groundwater level prediction within a deep learning framework: Incorporating the spatial dynamics of adjacent wells
Zhenyue Han, Fawen Li, Yong Zhao, et al.
Journal of Hydrology (2025), pp. 133097-133097
Closed Access
Performance enhancement of deep learning model with attention mechanism and FCN model in flood forecasting
Cheng Chen, Binquan Li, Huiming Zhang, et al.
Journal of Hydrology (2025), pp. 133221-133221
Closed Access
Identification of runner fatigue stages based on inertial sensors and deep learning
Pengfei Chang, Cenyi Wang, Yiyan Chen, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access | Times Cited: 9
A State-of-the-Art Review on Machine Learning Based Municipal Waste to Energy System
Dale Mark N. Bristol, Ivan Henderson V. Gue, Aristotle T. Ubando
Cleaner Energy Systems (2024) Vol. 9, pp. 100143-100143
Open Access | Times Cited: 3
Municipal Solid Waste Management Using Machine Learning: A Case Study in Sheger City, Koye Sub-city, Ethiopia
Tsegaye Hordofa Gudeta, Gudeta Tesema Mamo, Yezeshawal Mengistu Neguse
European Journal of Theoretical and Applied Sciences (2025) Vol. 3, Iss. 2, pp. 511-525
Closed Access
A Two-Stage transient stability prediction method using convolutional residual memory network and gated recurrent unit
Xianwen Zhan, Song Han, Na Rong, et al.
International Journal of Electrical Power & Energy Systems (2022) Vol. 138, pp. 107973-107973
Closed Access | Times Cited: 13
Deep learning hybrid predictions for the amount of municipal solid waste: A case study in Shanghai
Kunsen Lin, Youcai Zhao, Jia‐Hong Kuo
Chemosphere (2022) Vol. 307, pp. 136119-136119
Closed Access | Times Cited: 13
Machine learning tool-based prediction and forecasting of municipal solid waste generation rate: a case study in Guwahati, Assam, India
Thakur Monika Singh, R. Uppaluri
International Journal of Environmental Science and Technology (2022) Vol. 20, Iss. 11, pp. 12207-12230
Closed Access | Times Cited: 12
Solid waste mapping based on very high resolution remote sensing imagery and a novel deep learning approach
Bowen Niu, Quanlong Feng, Jianyu Yang, et al.
Geocarto International (2022) Vol. 38, Iss. 1
Open Access | Times Cited: 12
Long short-term memory neural network and improved particle swarm optimization–based modeling and scenario analysis for municipal solid waste generation in Shanghai, China
Deyun Wang, Ying-an Yuan, Yawen Ben, et al.
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 46, pp. 69472-69490
Open Access | Times Cited: 10
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