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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 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

Showing 1-25 of 32 citing articles:

Ensemble learning using multivariate variational mode decomposition based on the Transformer for multi-step-ahead streamflow forecasting
Jinjie Fang, Linshan Yang, Xiaohu Wen, et al.
Journal of Hydrology (2024) Vol. 636, pp. 131275-131275
Closed Access | Times Cited: 17
Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions
Shahid Latif, Maha Driss, Wadii Boulila, et al.
Sensors (2021) Vol. 21, Iss. 22, pp. 7518-7518
Open Access | Times Cited: 94
Hourly streamflow forecasting using a Bayesian additive regression tree model hybridized with a genetic algorithm
Duc Hai Nguyen, Xuan-Hien Le, Duong Tran Anh, et al.
Journal of Hydrology (2022) Vol. 606, pp. 127445-127445
Closed Access | Times Cited: 47
A hybrid deep learning approach for streamflow prediction utilizing watershed memory and process-based modeling
Bisrat Ayalew Yifru, Kyoung Jae Lim, Joo Hyun Bae, et al.
Hydrology Research (2024) Vol. 55, Iss. 4, pp. 498-518
Open Access | Times Cited: 9
River discharge prediction based multivariate climatological variables using hybridized long short-term memory with nature inspired algorithm
Sandeep Samantaray, Abinash Sahoo, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, et al.
Journal of Hydrology (2024), pp. 132453-132453
Closed Access | Times Cited: 6
Daily Streamflow Forecasting Using Networks of Real-Time Monitoring Stations and Hybrid Machine Learning Methods
Yue Zhang, Zimo Zhou, Ying Deng, et al.
Water (2024) Vol. 16, Iss. 9, pp. 1284-1284
Open Access | Times Cited: 5
High-Resolution Flow and Phosphorus Forecasting Using ANN Models, Catering for Extremes in the Case of the River Swale (UK)
Elisabeta Cristina Timiș, Horia Hangan, Mircea Vasile Cristea, et al.
Hydrology (2025) Vol. 12, Iss. 2, pp. 20-20
Open Access
Real-time streamflow forecasting: AI vs. Hydrologic insights
Witold F. Krajewski, Ganesh R. Ghimire, İbrahim Demir, et al.
Journal of Hydrology X (2021) Vol. 13, pp. 100110-100110
Open Access | Times Cited: 28
Decomposing the impacts of climate change and human activities on runoff changes in the Yangtze River Basin: Insights from regional differences and spatial correlations of multiple factors
Ting Chen, Lei Zou, Jun Xia, et al.
Journal of Hydrology (2022) Vol. 615, pp. 128649-128649
Closed Access | Times Cited: 20
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
A dynamic classification-based long short-term memory network model for daily streamflow forecasting in different climate regions
Haibo Chu, Jin Wu, Wenyan Wu, et al.
Ecological Indicators (2023) Vol. 148, pp. 110092-110092
Open Access | Times Cited: 11
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
Improving streamflow forecasting in semi-arid basins by combining data segmentation and attention-based deep learning
Zijie Tang, Jianyun Zhang, Mengliu Hu, et al.
Journal of Hydrology (2024) Vol. 643, pp. 131923-131923
Closed Access | Times Cited: 3
Investigating the potential of EMA-embedded feature selection method for ESVR and LSTM to enhance the robustness of monthly streamflow forecasting from local meteorological information
Lei Xu, Peng Shi, Hongshi Wu, et al.
Journal of Hydrology (2024) Vol. 636, pp. 131230-131230
Closed Access | Times Cited: 2
Improving deep learning-based streamflow forecasting under trend varying conditions through evaluation of new wavelet preprocessing technique
Mohammad Reza M. Behbahani, Maryam Mazarei, Amvrossios C. Bagtzoglou
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 10, pp. 3963-3984
Closed Access | Times Cited: 2
Enhancing hydrological predictions: optimised decision tree modelling for improved monthly inflow forecasting
Osama A. Abozweita, Ali Najah Ahmed, Lariyah Mohd Sidek, et al.
Journal of Hydroinformatics (2024)
Open Access | Times Cited: 2
State-of-the-Art Development of Two-Waves Artificial Intelligence Modeling Techniques for River Streamflow Forecasting
Woon Yang Tan, Sai Hin Lai, Fang Yenn Teo, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 7, pp. 5185-5211
Closed Access | Times Cited: 10
A Systematic Review of Deep Learning Applications in Streamflow Data Augmentation and Forecasting
Muhammed Sit, Bekir Zahit Demiray, İbrahim Demir
EarthArXiv (California Digital Library) (2022)
Open Access | Times Cited: 9
An attention mechanism-based deep regression approach with a sequence decomposition-granularity reconstruction-integration model for urban daily water supply forecasting
Yun Bai, Zhengjie Yan, Chuan Li
Journal of Hydrology (2022) Vol. 617, pp. 129032-129032
Closed Access | Times Cited: 8
The Performance Analysis of Robust Local Mean Mode Decomposition Method for Forecasting of Hydrological Time Series
Levent Latifoğlu
Iranian Journal of Science and Technology Transactions of Civil Engineering (2022) Vol. 46, Iss. 4, pp. 3453-3472
Closed Access | Times Cited: 6
Conceptual hydrological model-guided SVR approach for monthly lake level reconstruction in the Tibetan Plateau
Minglei Hou, Jiahua Wei, Haibo Chu, et al.
Journal of Hydrology Regional Studies (2022) Vol. 44, pp. 101271-101271
Open Access | Times Cited: 6
Improving Daily Streamflow Forecasting Using Deep Belief Net-Work Based on Flow Regime Recognition
Jianming Shen, Lei Zou, Yi Dong, et al.
Water (2022) Vol. 14, Iss. 14, pp. 2241-2241
Open Access | Times Cited: 5
A Probability Model for Short-Term Streamflow Prediction Based on Multi-Resolution Data
Lili Wang, Zexia Li, Fuqiang Ye, et al.
Water Resources Management (2023) Vol. 37, Iss. 14, pp. 5601-5618
Closed Access | Times Cited: 2
Deep‐learning based projection of change in irrigation water‐use under RCP 8.5
Jang Hyun Sung, Jinsoo Kim, ‪Eun‐Sung Chung, et al.
Hydrological Processes (2021) Vol. 35, Iss. 8
Closed Access | Times Cited: 5
A Review of Approaches and Applications for Streamflow Forecasting Using AI-Based Models
Manish K. Nema, G. E. Nagashree
(2024), pp. 17-33
Closed Access
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