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:

Short-term forecasts of streamflow in the UK based on a novel hybrid artificial intelligence algorithm
Fabio Di Nunno, Giovanni de Marinis, Francesco Granata
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

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
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao Hai, Sani I. Abba, Ahmed M. Al‐Areeq, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107559-107559
Closed Access | Times Cited: 58
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
An interpretable hybrid deep learning model for flood forecasting based on Transformer and LSTM
Wenzhong Li, Chengshuai Liu, Yingying Xu, et al.
Journal of Hydrology Regional Studies (2024) Vol. 54, pp. 101873-101873
Open Access | Times Cited: 15
Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
Jui‐Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, et al.
Natural hazards and earth system sciences (2025) Vol. 25, Iss. 1, pp. 119-146
Open Access | Times Cited: 1
A novel additive regression model for streamflow forecasting in German rivers
Francesco Granata, Fabio Di Nunno, Quoc Bao Pham
Results in Engineering (2024) Vol. 22, pp. 102104-102104
Open Access | Times Cited: 13
Forecasting short- and medium-term streamflow using stacked ensemble models and different meta-learners
Francesco Granata, Fabio Di Nunno
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 9, pp. 3481-3499
Closed Access | Times Cited: 8
Dissolved Oxygen Forecasting in the Mississippi River: Advanced Ensemble Machine Learning Models
Francesco Granata, Senlin Zhu, Fabio Di Nunno
Environmental Science Advances (2024) Vol. 3, Iss. 11, pp. 1537-1551
Open Access | Times Cited: 8
Advanced streamflow forecasting for Central European Rivers: The Cutting-Edge Kolmogorov-Arnold networks compared to Transformers
Francesco Granata, Senlin Zhu, Fabio Di Nunno
Journal of Hydrology (2024), pp. 132175-132175
Closed Access | Times Cited: 8
Assessing the performance and interpretability of the CNN-LSTM-Attention model for daily streamflow forecasting in typical basins of the eastern Qinghai-Tibet Plateau
Chuchu Zhang, Yuyan Zhou, Lu Fan, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Combining Synthetic and Observed Data to Enhance Machine Learning Model Performance for Streamflow Prediction
Sergio Ricardo López-Chacón, Fernando Salazar, Ernest Bladé
Water (2023) Vol. 15, Iss. 11, pp. 2020-2020
Open Access | Times Cited: 18
A novel optimized model based on NARX networks for predicting thermal anomalies in Polish lakes during heatwaves, with special reference to the 2018 heatwave
Senlin Zhu, Fabio Di Nunno, Mariusz Ptak, et al.
The Science of The Total Environment (2023) Vol. 905, pp. 167121-167121
Closed Access | Times Cited: 17
Interpretable machine learning scheme for predicting bridge pier scour depth
Taeyoon Kim, Azmayeen Rafat Shahriar, Woo-Dong Lee, et al.
Computers and Geotechnics (2024) Vol. 170, pp. 106302-106302
Closed Access | Times Cited: 7
A Combined Seasonal Mann–Kendall and Innovative Approach for the Trend Analysis of Streamflow Rate in Two Croatian Rivers
Mehmet Berkant Yıldız, Fabio Di Nunno, Bojan Ðurin, et al.
Water (2024) Vol. 16, Iss. 10, pp. 1422-1422
Open Access | Times Cited: 7
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: 5
Analysis of Data Splitting on Streamflow Prediction using Random Forest
Diksha Puri, Parveen Sihag, Mohindra Singh Thakur, et al.
AIMS environmental science (2024) Vol. 11, Iss. 4, pp. 593-609
Open Access | Times Cited: 4
Data-driven model as a post-process for daily streamflow prediction in ungauged basins
Jeonghyeon Choi, Sangdan Kim
Heliyon (2025) Vol. 11, Iss. 4, pp. e42512-e42512
Open Access
Exploring a long short-term memory for mountain flood forecasting based on watershed-internal knowledge graph and large language model
Songsong Wang, Ouguan Xu
PLoS ONE (2025) Vol. 20, Iss. 3, pp. e0318644-e0318644
Open Access
Streamflow Predictions in Ungauged Basins Using Recurrent Neural Network and Decision Tree-Based Algorithm: Application to the Southern Region of the Korean Peninsula
Jeongeun Won, Jiyu Seo, Jeonghoon Lee, et al.
Water (2023) Vol. 15, Iss. 13, pp. 2485-2485
Open Access | Times Cited: 8
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: 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
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
Analysis of land use/land cover changes and driving forces during the period 1992–2022: a case study of Jinan City, China
Lingye Tan, R. K., Ziyang Zhang
AQUA - Water Infrastructure Ecosystems and Society (2024) Vol. 73, Iss. 3, pp. 584-607
Open Access | Times Cited: 1
HCEG: A heterogeneous clustering ensemble learning approach with gravity-based strategy for data assets intelligent pricing
Jun Hao, Jiaxin Yuan, Jianping Li
Information Sciences (2024) Vol. 678, pp. 121082-121082
Closed Access | Times Cited: 1
Development of Functional Quantile Autoregressive Model for River Flow Curve Forecasting
Muge Mutis, Ufuk Beyaztaş, Gülhayat Gölbaşı Şimşek, et al.
Earth and Space Science (2024) Vol. 11, Iss. 8
Open Access | Times Cited: 1
Page 1 - Next Page

Scroll to top