Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 Comparative Study on Forecasting of Long-term Daily Streamflow using ANN, ANFIS, BiLSTM and CNN-GRU-LSTM
Sajjad M. Vatanchi, Hossein Etemadfard, Mahmoud F. Maghrebi, et al.
Water Resources Management (2023) Vol. 37, Iss. 12, pp. 4769-4785
Closed Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Recurrent Neural Networks: A Comprehensive Review of Architectures, Variants, and Applications
Ibomoiye Domor Mienye, Theo G. Swart, George Obaido
Information (2024) Vol. 15, Iss. 9, pp. 517-517
Open Access | Times Cited: 35
Evaluating the Performance of Several Data Preprocessing Methods Based on GRU in Forecasting Monthly Runoff Time Series
Wenchuan Wang, Yu-jin Du, Kwok‐wing Chau, et al.
Water Resources Management (2024) Vol. 38, Iss. 9, pp. 3135-3152
Open Access | Times Cited: 19
CEEMDAN-BILSTM-ANN and SVM Models: Two Robust Predictive Models for Predicting River flow
Elham Ghanbari-Adivi, Mohammad Ehteram
Water Resources Management (2025)
Closed Access | Times Cited: 2
Comparison of strategies for multistep-ahead lake water level forecasting using deep learning models
Gang Li, Zhangkang Shu, Miaoli Lin, et al.
Journal of Cleaner Production (2024) Vol. 444, pp. 141228-141228
Closed Access | Times Cited: 13
Daily suspended sediment yield estimation using soft-computing algorithms for hilly watersheds in a data-scarce situation: a case study of Bino watershed, Uttarakhand
Paramjeet Singh Tulla, Pravendra Kumar, Dinesh Kumar Vishwakarma, et al.
Theoretical and Applied Climatology (2024) Vol. 155, Iss. 5, pp. 4023-4047
Closed Access | Times Cited: 12
Enhancing Flooding Depth Forecasting Accuracy in an Urban Area Using a Novel Trend Forecasting Method
Song-Yue Yang, You-Da Jhong, Bing-Chen Jhong, et al.
Water Resources Management (2024) Vol. 38, Iss. 4, pp. 1359-1380
Closed Access | Times Cited: 11
Improving Hydrological Modeling with Hybrid Models: A Comparative Study of Different Mechanisms for Coupling Deep Learning Models with Process-based Models
Yiming Wei, Renchao Wang, Ping Feng
Water Resources Management (2024) Vol. 38, Iss. 7, pp. 2471-2488
Closed Access | Times Cited: 7
The Use of Attention-Enhanced CNN-LSTM Models for Multi-Indicator and Time-Series Predictions of Surface Water Quality
Minhao Zhang, Zhiyu Zhang, Xuan Wang, et al.
Water Resources Management (2024) Vol. 38, Iss. 15, pp. 6103-6119
Closed Access | Times Cited: 7
Deep learning algorithms and their fuzzy extensions for streamflow prediction in climate change framework
Rishith Kumar Vogeti, Rahul Jauhari, Bhavesh Rahul Mishra, et al.
Journal of Water and Climate Change (2024) Vol. 15, Iss. 2, pp. 832-848
Open Access | Times Cited: 5
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
Utilizing Deep Learning Models to Predict Streamflow
Habtamu Alemu Workneh, Manoj K. Jha
Water (2025) Vol. 17, Iss. 5, pp. 756-756
Open Access
Prediction of Qinghai Lake's level under future climate change: A hybrid modeling approach based on hydrological model and deep learning method
Kaixun Liu, Na Li, Sihai Liang
Journal of Hydrology Regional Studies (2025) Vol. 58, pp. 102283-102283
Open Access
Artificial Intelligence in Wind Turbine Fault Detection and Diagnosis: Advances and Perspectives
Nejad Alagha, Anis Salwa Mohd Khairuddin, Zineddine N. Haitaamar, et al.
Energies (2025) Vol. 18, Iss. 7, pp. 1680-1680
Open Access
Global Navigation Satellite System-Based Deformation Monitoring of Hydraulic Structures Using a Gated Recurrent Unit–Attention Mechanism
Haiyang Li, Yilin Xie, Azhong Dong, et al.
Remote Sensing (2025) Vol. 17, Iss. 8, pp. 1352-1352
Open Access
Leveraging deep learning for risk prediction and resilience in supply chains: insights from critical industries
Waleed Abdu Zogaan, Nouran Ajabnoor, Abdullah Ali Salamai
Journal Of Big Data (2025) Vol. 12, Iss. 1
Open Access
Extreme learning machine coupled with Heuristic algorithms for daily streamflow modeling at Lake Ziway Watershed, Ethiopia
Gebre Gelete, Hüseyin Gökçekuş, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, et al.
Journal of Hydrology (2025), pp. 133345-133345
Closed Access
Assessing the impacts of climate change on streamflow dynamics: A machine learning perspective
Mehran Khan, Afed Ullah Khan, Sunaid Khan, et al.
Water Science & Technology (2023) Vol. 88, Iss. 9, pp. 2309-2331
Open Access | Times Cited: 10
Assessing Objective Functions in Streamflow Prediction Model Training Based on the Naïve Method
Yongen Lin, Dagang Wang, Tao Jiang, et al.
Water (2024) Vol. 16, Iss. 5, pp. 777-777
Open Access | Times Cited: 2
Interpretable and explainable hybrid model for daily streamflow prediction based on multi-factor drivers
Wuyi Wan, Yu Zhou, Yaojie Chen
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 23, pp. 34588-34606
Closed Access | Times Cited: 2
Ensemble learning of decomposition-based machine learning models for multistep-ahead daily streamflow forecasting in northwest China
Haijiao Yu, Linshan Yang, Qi Feng, et al.
Hydrological Sciences Journal (2024) Vol. 69, Iss. 11, pp. 1501-1522
Closed 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
Optimizing river flow rate predictions: integrating cognitive approaches and meteorological insights
Veysi Kartal, Erkan Karakoyun, Muhammed Ernur Akıner, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 2
Harnessing Deep Learning and Snow Cover Data for Enhanced Runoff Prediction in Snow-Dominated Watersheds
Rana Muhammad Adnan Ikram, Mo Wang, Özgür Kişi, et al.
Atmosphere (2024) Vol. 15, Iss. 12, pp. 1407-1407
Open Access | Times Cited: 2
Enhanced variational mode decomposition with deep learning SVM kernels for river streamflow forecasting
S. N. Deepa, N. Natarajan, M. Berlin
Environmental Earth Sciences (2023) Vol. 82, Iss. 22
Closed Access | Times Cited: 4
Enhancing streamflow prediction in the Wujiang River basin: a two-stage decomposition approach with deep learning integration
Ruichao Zhao, Zhiwen Zheng
Journal of Water and Climate Change (2024) Vol. 15, Iss. 11, pp. 5683-5697
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top