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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 review of hybrid deep learning applications for streamflow forecasting
Kin‐Wang Ng, Yuk Feng Huang, Chai Hoon Koo, et al.
Journal of Hydrology (2023) Vol. 625, pp. 130141-130141
Closed Access | Times Cited: 72

Showing 26-50 of 72 citing articles:

Metamorphic testing of machine learning and conceptual hydrologic models
Peter Reichert, Kai Ma, Marvin Höge, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 11, pp. 2505-2529
Open Access | Times Cited: 4
Revolutionizing the Future of Hydrological Science: Impact of Machine Learning and Deep Learning amidst Emerging Explainable AI and Transfer Learning
Rajib Maity, Aman Srivastava, Subharthi Sarkar, et al.
Applied Computing and Geosciences (2024) Vol. 24, pp. 100206-100206
Open Access | Times Cited: 4
Advanced groundwater level forecasting with hybrid deep learning model: Tackling water challenges in Taiwan’s largest alluvial fan
Yu-Wen Chang, Wei Sun, Pu-Yun Kow, et al.
Journal of Hydrology (2025), pp. 132887-132887
Closed Access
Improve streamflow simulations by combining machine learning pre-processing and post-processing
Yuhang Zhang, Aizhong Ye, Jinyang Li, et al.
Journal of Hydrology (2025), pp. 132904-132904
Closed Access
Enhancing seasonal streamflow prediction using multistage hybrid stochastic data-driven deep learning methodology with deep feature selection
Asif Iqbal, Tanveer Ahmed Siddiqi
Environmental and Ecological Statistics (2025)
Closed Access
Protocols for Water and Environmental Modeling Using Machine Learning in California
Minxue He, Prabhjot Sandhu, Peyman Namadi, et al.
Hydrology (2025) Vol. 12, Iss. 3, pp. 59-59
Open Access
Predicting Ili River streamflow change and identifying the major drivers with a novel hybrid model
Shuang Liu, Aihua Long, Denghua Yan, et al.
Journal of Hydrology Regional Studies (2024) Vol. 53, pp. 101807-101807
Open Access | Times Cited: 3
Utilizing sequential modeling in collaborative method for flood forecasting
Wandee Thaisiam, Konlawat Yomwilai, Papis Wongchaisuwat
Journal of Hydrology (2024) Vol. 636, pp. 131290-131290
Closed Access | Times Cited: 3
Runoff Simulation in Data-Scarce Alpine Regions: Comparative Analysis Based on LSTM and Physically Based Models
Jiajia Yue, Li Zhou, Juan Du, et al.
Water (2024) Vol. 16, Iss. 15, pp. 2161-2161
Open Access | Times Cited: 3
Enhancing Subsurface Soil Moisture Forecasting: A Long Short-Term Memory Network Model Using Weather Data
Md. Samiul Basir, Samuel Noel, Dennis R. Buckmaster, et al.
Agriculture (2024) Vol. 14, Iss. 3, pp. 333-333
Open Access | Times Cited: 2
Optimizing Hybrid Renewable Energy Systems:Novel Models and Heuristic Algorithms
Eghbal Hosseini, Abbas M. Al-Ghaili, Muhammet Deveci, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 2
Uncertainty Forecasting Model for Mountain Flood Based on Bayesian Deep Learning
Songsong Wang, Ouguan Xu
IEEE Access (2024) Vol. 12, pp. 47830-47841
Open Access | Times Cited: 2
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
A parsimonious setup for streamflow forecasting using CNN-LSTM
Sudan Pokharel, Tirthankar Roy
Journal of Hydroinformatics (2024) Vol. 26, Iss. 11, pp. 2751-2761
Open Access | Times Cited: 2
Daily Runoff Forecasting Using Novel Optimized Machine Learning Methods
Peiman Parisouj, Changhyun Jun, Sayed M. Bateni, et al.
Results in Engineering (2024) Vol. 24, pp. 103319-103319
Open Access | Times Cited: 2
Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil
Gabriela Emiliana de Melo e Costa, Frederico Carlos Martins de Menezes Filho, Fausto A. Canales, et al.
Hydrology (2023) Vol. 10, Iss. 11, pp. 208-208
Open Access | Times Cited: 5
Combining Satellite Optical and Radar Image Data for Streamflow Estimation Using a Machine Learning Method
Xingcan Wang, Wenchao Sun, Fan Lü, et al.
Remote Sensing (2023) Vol. 15, Iss. 21, pp. 5184-5184
Open Access | Times Cited: 4
Multi-phase hybrid bidirectional deep learning model integrated with Markov chain Monte Carlo bivariate copulas function for streamflow prediction
Asif Iqbal, Tanveer Ahmed Siddiqi
Stochastic Environmental Research and Risk Assessment (2023) Vol. 38, Iss. 4, pp. 1351-1382
Closed Access | Times Cited: 4
Coupling Swat and Lstm for Improving Daily Streamflow Simulation in a Humid and Semi-Humid River Basin
Ziyi Mei, Tao Peng, Lü Chen, et al.
(2024)
Closed Access | Times Cited: 1
Machine learning applications in vadose zone hydrology: A review
Xiang Li, John L. Nieber, Vipin Kumar
Vadose Zone Journal (2024) Vol. 23, Iss. 4
Open Access | Times Cited: 1
Attribution of hydrological droughts in large river-connected lakes: Insights from an explainable machine learning model
Chenyang Xue, Qi Zhang, Yuxue Jia, et al.
The Science of The Total Environment (2024) Vol. 952, pp. 175999-175999
Closed Access | Times Cited: 1
Streamflow Prediction in Human‐Regulated Catchments Using Multiscale Deep Learning Modeling With Anthropogenic Similarities
Arken Tursun, Xianhong Xie, Yibing Wang, et al.
Water Resources Research (2024) Vol. 60, Iss. 9
Open Access | Times Cited: 1
Deep learning-based stability of quasi-integrable and non-resonant Hamiltonian systems driven by fractional Gaussian noise
Qiangfeng Lü, Weiqiu Zhu, Maolin Deng
The European Physical Journal Special Topics (2024)
Closed Access | Times Cited: 1

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