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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:

Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms
Khabat Khosravi, Ali Golkarian, John P. Tiefenbacher
Water Resources Management (2022) Vol. 36, Iss. 2, pp. 699-716
Closed Access | Times Cited: 61

Showing 26-50 of 61 citing articles:

Assessing influential rainfall–runoff variables to simulate daily streamflow using random forest
Federico Vilaseca, Alberto Castro, Christian Chreties, et al.
Hydrological Sciences Journal (2023) Vol. 68, Iss. 12, pp. 1738-1753
Closed Access | Times Cited: 9
Deep neural network-based discharge prediction for upstream hydrological stations: a comparative study
Xuan-Hien Le, Duc Hai Nguyen, Sungho Jung, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 3113-3124
Closed Access | Times Cited: 9
Assessing the reliability of a physical-based model and a convolutional neural network in an ungauged watershed for daily streamflow calculation: a case study in southern Portugal
Ana R. Oliveira, Tiago B. Ramos, Lucian Simionesei, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 7
Open Access | Times Cited: 3
Estimation of aquatic ecosystem health using deep neural network with nonlinear data mapping
Yong Sung Kwon, Hyeongsik Kang, JongCheol Pyo
Ecological Informatics (2024) Vol. 81, pp. 102588-102588
Open Access | Times Cited: 3
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
A Concurrent CNN-RNN Approach for Multi-step Wind Power Forecasting
Syed Kazmi
(2024)
Open Access | Times Cited: 3
Fueling the future: Exploring the synergy of artificial intelligence-based algorithms and the use of biofuels in engine development
Somya Patnaik, Narendra Khatri, Eldon R. Rene
Journal of the Taiwan Institute of Chemical Engineers (2024), pp. 105729-105729
Open Access | Times Cited: 3
Long-Term Streamflow Prediction Using Hybrid SVR-ANN Based on Bayesian Model Averaging
Mahdi Abbasi, Hossein Dehban, Ashkan Farokhnia, et al.
Journal of Hydrologic Engineering (2022) Vol. 27, Iss. 11
Closed Access | Times Cited: 14
Monthly streamflow prediction using hybrid extreme learning machine optimized by bat algorithm: a case study of Cheliff watershed, Algeria
Salah Difi, Yamina Elmeddahi, Aziz Hebal, et al.
Hydrological Sciences Journal (2022) Vol. 68, Iss. 2, pp. 189-208
Closed Access | Times Cited: 14
Monthly River Discharge Forecasting Using Hybrid Models Based on Extreme Gradient Boosting Coupled with Wavelet Theory and Lévy–Jaya Optimization Algorithm
Jincheng Zhou, Dan Wang, Shahab S. Band, et al.
Water Resources Management (2023) Vol. 37, Iss. 10, pp. 3953-3972
Closed Access | Times Cited: 8
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
RNN-Based Monthly Inflow Prediction for Dez Dam in Iran Considering the Effect of Wavelet Pre-Processing and Uncertainty Analysis
Arash Adib, Mohammad Pourghasemzadeh, Morteza Lotfirad
Hydrology (2024) Vol. 11, Iss. 9, pp. 155-155
Open Access | Times Cited: 2
Predicting Daily Streamflow in a Cold Climate Using a Novel Data Mining Technique: Radial M5 Model Tree
Özgür Kişi, Salim Heddam, Behrooz Keshtegar, et al.
Water (2022) Vol. 14, Iss. 9, pp. 1449-1449
Open Access | Times Cited: 12
Data-Driven Dam Outflow Prediction Using Deep Learning with Simultaneous Selection of Input Predictors and Hyperparameters Using the Bayesian Optimization Algorithm
Vinh Ngoc Tran, Duc Dang Dinh, Binh Duy Huy Pham, et al.
Water Resources Management (2023) Vol. 38, Iss. 2, pp. 401-421
Closed Access | Times Cited: 6
River Flow Modeling in Semi-Arid and Humid Regions Using an Integrated Method Based on LARS-WG and LSTM Models
Kiyoumars Roushangar, Sadegh Abdelzad
Water Resources Management (2023) Vol. 37, Iss. 10, pp. 3813-3831
Closed Access | Times Cited: 6
Cascade reservoirs operation rules derivation using integrated decision-making method and combinatorial evolution network
Xinliang Qi, Hui Qin, Sainan Jiang, et al.
Journal of Cleaner Production (2023) Vol. 414, pp. 137608-137608
Closed Access | Times Cited: 6
Simulated annealing coupled with a Naïve Bayes model and base flow separation for streamflow simulation in a snow dominated basin
Hakan Tongal, Martijn J. Booij
Stochastic Environmental Research and Risk Assessment (2022) Vol. 37, Iss. 1, pp. 89-112
Closed Access | Times Cited: 9
Three Steps towards Better Forecasting for Streamflow Deep Learning
Woon Yang Tan, Sai Hin Lai, Fang Yenn Teo, et al.
Applied Sciences (2022) Vol. 12, Iss. 24, pp. 12567-12567
Open Access | Times Cited: 9
A deep learning workflow enhanced with optical flow fields for flood risk estimation
Caetano Mazzoni Ranieri, Thaís Luiza Donega e Souza, Marislei Nishijima, et al.
Applied Intelligence (2024) Vol. 54, Iss. 7, pp. 5536-5557
Closed Access | Times Cited: 1
Variational mode decomposition coupled LSTM with encoder-decoder framework: an efficient method for daily streamflow forecasting
Jiadong Liu, Teng Xu, Chunhui Lu, et al.
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access | Times Cited: 1
Comparison and integration of hydrological models and machine learning models in global monthly streamflow simulation
Jiawen Zhang, Dongdong Kong, Jianfeng Li, et al.
Journal of Hydrology (2024), pp. 132549-132549
Closed Access | Times Cited: 1
Comparative assessment of advanced machine learning techniques for simulation of lake water level fluctuations based on different dimensionality reduction methods
Mostafa Riazi, Maryam Karimi, Saeid Eslamian, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 37-55
Closed Access | Times Cited: 3
Data‐driven artificial intelligence‐based streamflow forecasting, a review of methods, applications, and tools
Heerbod Jahanbani, Khandakar Ahmed, Bruce Gu
JAWRA Journal of the American Water Resources Association (2024)
Open Access
Multiple-model based prediction of weekly discharge of the Brahmaputra-Jamuna by assimilating antecedent hydrological regime
Md Abdur Rahim, Shuang Liu, Kaiheng Hu, et al.
Geocarto International (2024) Vol. 39, Iss. 1
Open Access
Approximation in scour depth around spur dikes using novel hybrid ensemble data-driven model
Balraj Singh, Vijay K. Minocha
Water Science & Technology (2024) Vol. 89, Iss. 4, pp. 962-975
Open Access

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