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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:

Streamflow prediction using LASSO-FCM-DBN approach based on hydro-meteorological condition classification
Haibo Chu, Jiahua Wei, Wenyan Wu
Journal of Hydrology (2019) Vol. 580, pp. 124253-124253
Closed Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

A physical process and machine learning combined hydrological model for daily streamflow simulations of large watersheds with limited observation data
Shuyu Yang, Dawen Yang, Jinsong Chen, et al.
Journal of Hydrology (2020) Vol. 590, pp. 125206-125206
Open Access | Times Cited: 183
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
A. A. Masrur Ahmed, Ravinesh C. Deo, Qi Feng, et al.
Journal of Hydrology (2021) Vol. 599, pp. 126350-126350
Closed Access | Times Cited: 112
A Comprehensive Survey of Machine Learning Methodologies with Emphasis in Water Resources Management
Maria Drogkoula, Konstantinos Kokkinos, Nicholas Samaras
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12147-12147
Open Access | Times Cited: 47
Coupling Deep Learning and Physically Based Hydrological Models for Monthly Streamflow Predictions
Wenxin Xu, Jie Chen, Gerald Corzo, et al.
Water Resources Research (2024) Vol. 60, Iss. 2
Open Access | Times Cited: 16
Reconstructing Long-Term Daily Streamflow Data at the Discontinuous Monitoring Station in the Ungauged Transboundary Basin Using Machine Learning
Vinh Ngoc Tran, Thi Thuy Hang Nguyen, Hai Van Khuong, et al.
Water Resources Management (2025)
Closed Access | Times Cited: 2
New double decomposition deep learning methods for river water level forecasting
A. A. Masrur Ahmed, Ravinesh C. Deo, Afshin Ghahramani, et al.
The Science of The Total Environment (2022) Vol. 831, pp. 154722-154722
Closed Access | Times Cited: 48
Identifying major drivers of daily streamflow from large-scale atmospheric circulation with machine learning
Jenny Sjåstad Hagen, Étienne Leblois, Deborah Lawrence, et al.
Journal of Hydrology (2021) Vol. 596, pp. 126086-126086
Open Access | Times Cited: 51
A Regional Semi-Distributed Streamflow Model Using Deep Learning
Zhongrun Xiang, İbrahim Demir, Ricardo Mantilla, et al.
EarthArXiv (California Digital Library) (2021)
Open Access | Times Cited: 47
Streamflow forecasting
Priyanka Sharma, Deepesh Machiwal
Elsevier eBooks (2021), pp. 1-50
Closed Access | Times Cited: 42
Spatiotemporal deep learning rainfall-runoff forecasting combined with remote sensing precipitation products in large scale basins
Shuang Zhu, Jianan Wei, Hairong Zhang, et al.
Journal of Hydrology (2022) Vol. 616, pp. 128727-128727
Closed Access | Times Cited: 34
Application of Long Short-Term Memory (LSTM) on the Prediction of Rainfall-Runoff in Karst Area
Longzhang Fang, Dongguo Shao
Frontiers in Physics (2022) Vol. 9
Open Access | Times Cited: 33
Machine Learning Methods to Forecast the Concentration of PM10 in Lublin, Poland
Justyna Kujawska, Monika Kulisz, Piotr Oleszczuk, et al.
Energies (2022) Vol. 15, Iss. 17, pp. 6428-6428
Open Access | Times Cited: 29
A novel axle temperature forecasting method based on decomposition, reinforcement learning optimization and neural network
Hui Liu, Chengming Yu, Chengqing Yu, et al.
Advanced Engineering Informatics (2020) Vol. 44, pp. 101089-101089
Open Access | Times Cited: 44
The 63-year changes in annual streamflow volumes across Europe with a focus on the Mediterranean basin
Daniele Masseroni, Stefania Camici, Alessio Cislaghi, et al.
Hydrology and earth system sciences (2021) Vol. 25, Iss. 10, pp. 5589-5601
Open Access | Times Cited: 36
A classification-based deep belief networks model framework for daily streamflow forecasting
Haibo Chu, Jiahua Wei, Wenyan Wu, et al.
Journal of Hydrology (2021) Vol. 595, pp. 125967-125967
Closed Access | Times Cited: 32
A framework of integrating heterogeneous data sources for monthly streamflow prediction using a state-of-the-art deep learning model
Wenxin Xu, Jie Chen, XC Zhang, et al.
Journal of Hydrology (2022) Vol. 614, pp. 128599-128599
Closed Access | Times Cited: 24
A Comparative Assessment of Six Machine Learning Models for Prediction of Bending Force in Hot Strip Rolling Process
Xu Li, Feng Luan, Yan Wu
Metals (2020) Vol. 10, Iss. 5, pp. 685-685
Open Access | Times Cited: 34
Approaches for the short-term prediction of natural daily streamflows using hybrid machine learning enhanced with grey wolf optimization
Alfeu D. Martinho, Camila Martins Saporetti, Leonardo Goliatt
Hydrological Sciences Journal (2022) Vol. 68, Iss. 1, pp. 16-33
Closed Access | Times Cited: 19
Examination and comparison of binary metaheuristic wrapper-based input variable selection for local and global climate information-driven one-step monthly streamflow forecasting
Kun Ren, Xue Wang, Xiaoyu Shi, et al.
Journal of Hydrology (2021) Vol. 597, pp. 126152-126152
Closed Access | Times Cited: 24
The development of dissolved oxygen forecast model using hybrid machine learning algorithm with hydro-meteorological variables
A. A. Masrur Ahmed, S. Janifer Jabin Jui, Mohammad Aktarul Islam Chowdhury, et al.
Environmental Science and Pollution Research (2022) Vol. 30, Iss. 3, pp. 7851-7873
Open Access | Times Cited: 18
Water quality prediction of artificial intelligence model: a case of Huaihe River Basin, China
Jing Chen, H. Li, Manirankunda Felix, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 10, pp. 14610-14640
Closed Access | Times Cited: 3
Enhancing the streamflow simulation of a process-based hydrological model using machine learning and multi-source data
Huajin Lei, Hongyi Li, Wanpin Hu
Ecological Informatics (2024) Vol. 82, pp. 102755-102755
Open Access | Times Cited: 3
Development of a Joint Probabilistic Rainfall‐Runoff Model for High‐to‐Extreme Flow Projections Under Changing Climatic Conditions
Kailong Li, Guohe Huang, Shuo Wang, et al.
Water Resources Research (2022) Vol. 58, Iss. 6
Closed Access | Times Cited: 13
Hybrid Approach for Streamflow Prediction: LASSO-Hampel Filter Integration with Support Vector Machines, Artificial Neural Networks, and Autoregressive Distributed Lag Models
Maha Shabbir, Sohail Chand, Farhat Iqbal, et al.
Water Resources Management (2024) Vol. 38, Iss. 11, pp. 4179-4196
Closed Access | Times Cited: 2
Enhancing short-term streamflow prediction in the Haihe River Basin through integrated machine learning with Lasso
Yongyu Song, Jing Zhang
Water Science & Technology (2024) Vol. 89, Iss. 9, pp. 2367-2383
Open Access | Times Cited: 2
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