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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 deep learning approach for hydrological time-series prediction: A case study of Gilgit river basin
Dostdar Hussain, Tahir Hussain, Aftab Ahmed Khan, et al.
Earth Science Informatics (2020) Vol. 13, Iss. 3, pp. 915-927
Closed Access | Times Cited: 116

Showing 1-25 of 116 citing articles:

Urban flood modeling using deep-learning approaches in Seoul, South Korea
Xinxiang Lei, Wei Chen, Mahdi Panahi, et al.
Journal of Hydrology (2021) Vol. 601, pp. 126684-126684
Open Access | Times Cited: 152
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: 77
Recent Advances and New Frontiers in Riverine and Coastal Flood Modeling
Keighobad Jafarzadegan, Hamid Moradkhani, Florian Pappenberger, et al.
Reviews of Geophysics (2023) Vol. 61, Iss. 2
Open Access | Times Cited: 67
Machine-learning- and deep-learning-based streamflow prediction in a hilly catchment for future scenarios using CMIP6 GCM data
Dharmaveer Singh, Manu Vardhan, Rakesh Sahu, et al.
Hydrology and earth system sciences (2023) Vol. 27, Iss. 5, pp. 1047-1075
Open Access | Times Cited: 52
A comprehensive study of deep learning for soil moisture prediction
Yanling Wang, Liangsheng Shi, Yaan Hu, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 4, pp. 917-943
Open Access | Times Cited: 15
Monthly Streamflow Forecasting Using Convolutional Neural Network
Xingsheng Shu, Wei Ding, Yong Peng, et al.
Water Resources Management (2021) Vol. 35, Iss. 15, pp. 5089-5104
Open Access | Times Cited: 71
Stacking ensemble learning models for daily runoff prediction using 1D and 2D CNNs
Yutong Xie, Wei Sun, Miaomiao Ren, et al.
Expert Systems with Applications (2022) Vol. 217, pp. 119469-119469
Closed Access | Times Cited: 67
Karst spring discharge modeling based on deep learning using spatially distributed input data
Andreas Wünsch, Tanja Liesch, Guillaume Cinkus, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 9, pp. 2405-2430
Open Access | Times Cited: 40
Development of Machine Learning Flood Model Using Artificial Neural Network (ANN) at Var River
Mumtaz Ahmad, Md Abdullah Al Mehedi, Munshi Md. Shafwat Yazdan, et al.
Liquids (2022) Vol. 2, Iss. 3, pp. 147-160
Open Access | Times Cited: 39
A review of deep learning and machine learning techniques for hydrological inflow forecasting
Sarmad Dashti Latif, Ali Najah Ahmed
Environment Development and Sustainability (2023) Vol. 25, Iss. 11, pp. 12189-12216
Closed Access | Times Cited: 30
A Novel Smoothing-Based Deep Learning Time-Series Approach for Daily Suspended Sediment Load Prediction
Bibhuti Bhusan Sahoo, Sovan Sankalp, Özgür Kişi
Water Resources Management (2023) Vol. 37, Iss. 11, pp. 4271-4292
Closed Access | Times Cited: 25
Application of machine learning and emerging remote sensing techniques in hydrology: A state-of-the-art review and current research trends
Asish Saha, Subodh Chandra Pal
Journal of Hydrology (2024) Vol. 632, pp. 130907-130907
Closed Access | Times Cited: 13
Quick large-scale spatiotemporal flood inundation computation using integrated Encoder-Decoder LSTM with time distributed spatial output models
Guozhen Wei, Wei Xia, Bin He, et al.
Journal of Hydrology (2024) Vol. 634, pp. 130993-130993
Closed Access | Times Cited: 9
Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands
Faisal Mehmood Butt, Lal Hussain, Anzar Mahmood, et al.
Mathematical Biosciences & Engineering (2020) Vol. 18, Iss. 1, pp. 400-425
Open Access | Times Cited: 50
Evaluation and interpretation of convolutional long short-term memory networks for regional hydrological modelling
Sam Anderson, Valentina Radić
Hydrology and earth system sciences (2022) Vol. 26, Iss. 3, pp. 795-825
Open Access | Times Cited: 34
Prediction of sunflower grain yield under normal and salinity stress by RBF, MLP and, CNN models
Sanaz Khalifani, Reza Darvishzadeh, Nasrin Azad, et al.
Industrial Crops and Products (2022) Vol. 189, pp. 115762-115762
Closed Access | Times Cited: 33
The Short-Term Prediction of Length of Day Using 1D Convolutional Neural Networks (1D CNN)
Sonia Guessoum, Santiago Belda, José M. Ferrándiz, et al.
Sensors (2022) Vol. 22, Iss. 23, pp. 9517-9517
Open Access | Times Cited: 29
Geospatial Artificial Intelligence (GeoAI) in the Integrated Hydrological and Fluvial Systems Modeling: Review of Current Applications and Trends
Carlos Gonzales‐Inca, Mikel Calle, Danny Croghan, et al.
Water (2022) Vol. 14, Iss. 14, pp. 2211-2211
Open Access | Times Cited: 28
A comparative study of Machine Learning and Deep Learning methods for flood forecasting in the Far-North region, Cameroon
Francis Yongwa Dtissibe, Ado Adamou Abba Ari, Hamadjam Abboubakar, et al.
Scientific African (2023) Vol. 23, pp. e02053-e02053
Open Access | Times Cited: 21
Deep Learning Parameterization of the Tropical Cyclone Boundary Layer
Le‐Yi Wang, Zhe‐Min Tan
Journal of Advances in Modeling Earth Systems (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 17
Monthly runoff time series interval prediction based on WOA-VMD-LSTM using non-parametric kernel density estimation
Wenchuan Wang, Bo Wang, Kwok‐wing Chau, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 3, pp. 2373-2389
Closed Access | Times Cited: 17
Daily scale streamflow forecasting in multiple stream orders of Cauvery River, India: Application of advanced ensemble and deep learning models
Sujay Raghavendra Naganna, Sreedhara B. Marulasiddappa, Muttana S. Balreddy, et al.
Journal of Hydrology (2023) Vol. 626, pp. 130320-130320
Closed Access | Times Cited: 17
Deep Learning Model Effectiveness in Forecasting Limited-Size Aboveground Vegetation Biomass Time Series: Kenyan Grasslands Case Study
Efrain Noa-Yarasca, Javier M. Osorio Leyton, Jay P. Angerer
Agronomy (2024) Vol. 14, Iss. 2, pp. 349-349
Open Access | Times Cited: 6
Spatiotemporal estimation of groundwater and surface water conditions by integrating deep learning and physics-based watershed models
Soobin Kim, Eunhee Lee, Hyoun‐Tae Hwang, et al.
Water Research X (2024) Vol. 23, pp. 100228-100228
Open Access | Times Cited: 6
Alkali-activated binder concrete strength prediction using hybrid-deep learning along with shapely additive explanations and uncertainty analysis
Pobithra Das, Abul Kashem, Mominul Islam, et al.
Construction and Building Materials (2024) Vol. 435, pp. 136711-136711
Closed Access | Times Cited: 6
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