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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:

Multi-step Ahead Urban Water Demand Forecasting Using Deep Learning Models
Bibhuti Bhusan Sahoo, Banamali Panigrahi, Trushnamayee Nanda, et al.
SN Computer Science (2023) Vol. 4, Iss. 6
Closed Access | Times Cited: 20

Showing 20 citing articles:

Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm
Masoud Karbasi, Mumtaz Ali, Sayed M. Bateni, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 9
Multi-step forecasting of dissolved oxygen in River Ganga based on CEEMDAN-AdaBoost-BiLSTM-LSTM model
Neha Pant, Durga Toshniwal, Bhola Ram Gurjar
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Prediction of reservoir evaporation considering water temperature and using ANFIS hybridized with metaheuristic algorithms
Boudjerda Marouane, Mu’azu Mohammed Abdullahi, Andrea Petroselli‬
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1779-1798
Closed Access | Times Cited: 4
Exploring the applicability of the experiment-based ANN and LSTM models for streamflow estimation
Muhammed Ernur Akıner, Veysi Kartal, Anıl Can Güzeler, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 4, pp. 3111-3135
Open Access | Times Cited: 4
Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas
Owais Ali Wani, Syed Sheraz Mahdi, Md Yeasin, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Dependency Tree-Integrator Method for Reducing Mislaid Data Errors in Water Demand Prediction
G Manikannan, K. Jayanthi
Research Square (Research Square) (2025)
Closed Access
A Case Study on Water Demand Forecasting in a Coastal Tourist City
Antoniel Kleber Stefaniak, Pablo Andretta Jaskowiak, Lucas Weihmann
Lecture notes in computer science (2025), pp. 3-17
Closed Access
Streamflow prediction using Long Short-Term Memory networks: a case study at the Kratie Hydrological Station, Mekong River Basin
Nhu Y Nguyen, Dinh Kha Dang, Luu Van Ninh, et al.
Journal of Hydroinformatics (2025)
Open Access
Hybrid deep learning models for multi-ahead river water level forecasting
Abul Kashem, Pobithra Das, Md. Mahmudul Hasan, et al.
Earth Science Informatics (2024) Vol. 17, Iss. 4, pp. 3021-3037
Closed Access | Times Cited: 3
Predicting mine water inflow volumes using a decomposition-optimization algorithm-machine learning approach
Jiaxin Bian, Tao Hou, Dengjun Ren, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
A SOM-LSTM combined model for groundwater level prediction in karst critical zone aquifers considering connectivity characteristics
Fei Guo, Shilong Li, Gang Zhao, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 9
Open Access | Times Cited: 2
Applications of Artificial Intelligence for Demand Forecasting
Thi Thuy Hanh Nguyen
Operations and Supply Chain Management An International Journal (2023), pp. 424-434
Open Access | Times Cited: 5
Hydrological time series prediction based on IWOA-ALSTM
Xuejie Zhang, Hao Cang, Nadia Nedjah, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Global monthly sea surface temperature forecasting using the SARIMA, LSTM, and GRU models
Mehmet Bilgili, Engin Pınar, Tahir Durhasan
Earth Science Informatics (2024) Vol. 18, Iss. 1
Closed Access | Times Cited: 1
A maximal overlap discrete wavelet packet transform coupled with an LSTM deep learning model for improving multilevel groundwater level forecasts
Dilip Kumar Roy, Ahmed A. Hashem, Michele L. Reba, et al.
Discover Water (2024) Vol. 4, Iss. 1
Open Access
Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living
Manar Ahmed Hamza, Aisha Hassan Abdalla Hashim, Abdelwahed Motwakel, et al.
SN Computer Science (2024) Vol. 5, Iss. 5
Closed Access
Combining wavelet-enhanced feature selection and deep learning techniques for multi-step forecasting of urban water demand
Wenjin Hao, Andrea Cominola, Andrea Castelletti
Environmental Research Infrastructure and Sustainability (2024) Vol. 4, Iss. 3, pp. 035005-035005
Open Access
A novel hybrid approach based on outlier and error correction methods to predict river discharge using meteorological variables
Maha Shabbir, Sohail Chand, Farhat Iqbal
Environmental and Ecological Statistics (2024)
Closed Access
A novel optimized coupled runoff model is developed based on the concept of “decomposition-prediction-reconstruction”
Xianqi Zhang, Yupeng Zheng, Yang Yang, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 22
Closed Access
A Container Cloud Elastic Scaling Method Based on GRU Attention Mechanism
Yue Zhang, Yong Sun, Chunhe Song, et al.
(2024), pp. 290-293
Closed Access
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