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:

Daily flow discharge prediction using integrated methodology based on LSTM models: Case study in Brahmani-Baitarani basin
Abinash Sahoo, Swayamshu Satyapragnya Parida, Sandeep Samantaray, et al.
HydroResearch (2024) Vol. 7, pp. 272-284
Open Access | Times Cited: 15

Showing 15 citing articles:

Streamflow Simulation Using a Hybrid Approach Combining HEC-HMS and LSTM Model in the Tlawng River Basin of Mizoram, India
Sagar Debbarma, Arnab Bandyopadhyay, Aditi Bhadra
Environmental Modeling & Assessment (2025)
Closed Access

Intercomparison of sediment transport curve and novel deep learning techniques in simulating sediment transport in the Wadi Mina Basin, Algeria
Mohammed Achite, Okan Mert Katipoğlu, Nehal Elshaboury, et al.
Environmental Earth Sciences (2025) Vol. 84, Iss. 2
Closed Access

An improved support vector machine model for groundwater level prediction: a case study
Sasmita Sahoo, Deba Prakash Satapathy
Earth Science Informatics (2025) Vol. 18, Iss. 1
Closed Access

Advanced deep learning approaches for superior temporal analysis and forecasting of water level discharge for the Bamni River
S. S. Lachure, Ashish Tiwari
International Journal of River Basin Management (2025), pp. 1-19
Closed Access

Artificial Intelligence in Hydrology: Advancements in Soil, Water Resource Management, and Sustainable Development
Seyed Mostafa Biazar, Golmar Golmohammadi, Rohit R. Nedhunuri, et al.
Sustainability (2025) Vol. 17, Iss. 5, pp. 2250-2250
Open Access

Machine Learning Approaches for Assessing Groundwater Quality and Its Implications for Water Conservation in the Sub-tropical Capital Region of India
Nand Lal Kushwaha, Madhumita Sahoo, Nilesh Biwalkar
Water Conservation Science and Engineering (2025) Vol. 10, Iss. 1
Closed Access

Exploring PM2.5 and PM10 ML forecasting models: a comparative study in the UAE
Waad Abuouelezz, Nazar Ali, Zeyar Aung, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access

Day-ahead photovoltaic power generation forecasting with the HWGC-WPD-LSTM hybrid model assisted by wavelet packet decomposition and improved similar day method
Ruxue Bai, Jinsong Li, Jinsong Liu, et al.
Engineering Science and Technology an International Journal (2024) Vol. 61, pp. 101889-101889
Open Access | Times Cited: 1

Accurate estimation of Jujube leaf chlorophyll content using optimized spectral indices and machine learning methods integrating geospatial information
Nigela Tuerxun, Sulei Naibi, Jianghua Zheng, et al.
Ecological Informatics (2024), pp. 102980-102980
Open Access | Times Cited: 1

Performance analysis of machine learning models for AQI prediction in Gorakhpur City: a critical study
Mandvi, Prabhat Kumar Patel, Hrishikesh Kumar Singh
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 10
Closed Access

GWO-ANFIS-RD3PG: A reinforcement learning approach with dynamic adjustment and dual replay mechanism for building energy forecasting
Xiang Ma, Jie Fan, Jian Wang, et al.
Journal of Building Engineering (2024), pp. 110726-110726
Closed 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

Predicting ignitability classification of thermally thick solids using hybrid GA-BPNN and PSO-BPNN algorithms
Anran Sun, Xuguang Tang, Huilian Liao, et al.
Fuel (2024) Vol. 381, pp. 133474-133474
Closed Access

Development of deep learning approaches for drought forecasting: a comparative study in a cold and semi-arid region
Amin Gharehbaghi, Redvan Ghasemlounıa, Babak Vaheddoost, et al.
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access

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