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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:

Flood prediction based on weather parameters using deep learning
Suresh Sankaranarayanan, Malavika Prabhakar, Sreesta Satish, et al.
Journal of Water and Climate Change (2019) Vol. 11, Iss. 4, pp. 1766-1783
Closed Access | Times Cited: 113

Showing 1-25 of 113 citing articles:

A comprehensive review of deep learning applications in hydrology and water resources
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang, et al.
Water Science & Technology (2020) Vol. 82, Iss. 12, pp. 2635-2670
Open Access | Times Cited: 395
Applications of artificial intelligence for disaster management
Wenjuan Sun, Paolo Bocchini, Brian D. Davison
Natural Hazards (2020) Vol. 103, Iss. 3, pp. 2631-2689
Closed Access | Times Cited: 289
Machine Learning in Disaster Management: Recent Developments in Methods and Applications
Vasileios Linardos, Maria Drakaki, Panagiotis Tzionas, et al.
Machine Learning and Knowledge Extraction (2022) Vol. 4, Iss. 2, pp. 446-473
Open Access | Times Cited: 135
Comprehensive Review: Advancements in Rainfall-Runoff Modelling for Flood Mitigation
Muhammad Jehanzaib, Muhammad Ajmal, Mohammed Achite, et al.
Climate (2022) Vol. 10, Iss. 10, pp. 147-147
Open Access | Times Cited: 69
Adapting cities to the surge: A comprehensive review of climate-induced urban flooding
Gangani Dharmarathne, Anushka Osadhi Waduge, Madhusha Bogahawaththa, et al.
Results in Engineering (2024) Vol. 22, pp. 102123-102123
Open Access | Times Cited: 42
A review on flood management technologies related to image processing and machine learning
Hafiz Suliman Munawar, Ahmed W. A. Hammad, S. Travis Waller
Automation in Construction (2021) Vol. 132, pp. 103916-103916
Closed Access | Times Cited: 94
UAVs in Disaster Management: Application of Integrated Aerial Imagery and Convolutional Neural Network for Flood Detection
Hafiz Suliman Munawar, Fahim Ullah, Siddra Qayyum, et al.
Sustainability (2021) Vol. 13, Iss. 14, pp. 7547-7547
Open Access | Times Cited: 90
Application of machine learning algorithms for flood susceptibility assessment and risk management
R. Madhuri, Saiteja Sistla, K. Srinivasa Raju
Journal of Water and Climate Change (2021) Vol. 12, Iss. 6, pp. 2608-2623
Open Access | Times Cited: 64
Flood Forecasting by Using Machine Learning: A Study Leveraging Historic Climatic Records of Bangladesh
Adel Rajab, Hira Farman, Noman Islam, et al.
Water (2023) Vol. 15, Iss. 22, pp. 3970-3970
Open Access | Times Cited: 33
FFM: Flood Forecasting Model Using Federated Learning
Muhammad Shoaib Farooq, Rabia Tehseen, Junaid Nasir Qureshi, et al.
IEEE Access (2023) Vol. 11, pp. 24472-24483
Open Access | Times Cited: 26
Know to Predict, Forecast to Warn: A Review of Flood Risk Prediction Tools
Kwesi Twum Antwi-Agyakwa, Mawuli Afenyo, Donatus Bapentire Angnuureng
Water (2023) Vol. 15, Iss. 3, pp. 427-427
Open Access | Times Cited: 23
An Improved Flood Susceptibility Assessment in Jeddah, Saudi Arabia, Using Advanced Machine Learning Techniques
Abdulnoor A. J. Ghanim, Ahmad Shaf, Tariq Ali, et al.
Water (2023) Vol. 15, Iss. 14, pp. 2511-2511
Open Access | Times Cited: 23
Stochastic modeling of artificial neural networks for real-time hydrological forecasts based on uncertainties in transfer functions and ANN weights
Shiang‐Jen Wu, Chih‐Tsung Hsu, Che-Hao Chang
Hydrology Research (2024)
Open Access | Times Cited: 9
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources
Muhammed Sit, Bekir Zahit Demiray, Zhongrun Xiang, et al.
EarthArXiv (California Digital Library) (2020)
Open Access | Times Cited: 54
A new approach of deep neural computing for spatial prediction of wildfire danger at tropical climate areas
Van Hung Le, Duc A. Hoang, Chuyen Trung Tran, et al.
Ecological Informatics (2021) Vol. 63, pp. 101300-101300
Closed Access | Times Cited: 54
Prediction of Flood in Barak River using Hybrid Machine Learning Approaches: A Case Study
Abinash Sahoo, Sandeep Samantaray, Dillip K. Ghose
Journal of the Geological Society of India (2021) Vol. 97, Iss. 2, pp. 186-198
Closed Access | Times Cited: 53
Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney, Melbourne and Brisbane
Nayomi Kankanamge, Tan Yiğitcanlar, Ashantha Goonetilleke
Telematics and Informatics (2021) Vol. 65, pp. 101729-101729
Open Access | Times Cited: 43
Spatial Analysis of Flood Hazard Zoning Map Using Novel Hybrid Machine Learning Technique in Assam, India
Chiranjit Singha, Kishore Chandra Swain, Modeste Meliho, et al.
Remote Sensing (2022) Vol. 14, Iss. 24, pp. 6229-6229
Open Access | Times Cited: 31
Prediction of monthly precipitation using various artificial models and comparison with mathematical models
Youssef Kassem, Hüseyin Gökçekuş, Almonsef Alhadi Salem Mosbah
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 14, pp. 41209-41235
Closed Access | Times Cited: 18
Enhanced machine learning models development for flash flood mapping using geospatial data
Yacine Hasnaoui, Salah Eddine Tachi, Hamza Bouguerra, et al.
Euro-Mediterranean Journal for Environmental Integration (2024) Vol. 9, Iss. 3, pp. 1087-1107
Closed Access | Times Cited: 7
Applying Machine Learning Methods to Improve Rainfall–Runoff Modeling in Subtropical River Basins
Haoyuan Yu, Qichun Yang
Water (2024) Vol. 16, Iss. 15, pp. 2199-2199
Open Access | Times Cited: 6
Enhancing Flood Risk Mitigation by Advanced Data-Driven Approach
Ali S. Chafjiri, Mohammad Gheibi, Benyamin Chahkandi, et al.
Heliyon (2024) Vol. 10, Iss. 18, pp. e37758-e37758
Open Access | Times Cited: 6
A hybrid deep learning model for predictive flood warning and situation awareness using channel network sensors data
Shangjia Dong, Tianbo Yu, Hamed Farahmand, et al.
Computer-Aided Civil and Infrastructure Engineering (2020) Vol. 36, Iss. 4, pp. 402-420
Open Access | Times Cited: 49
A network percolation-based contagion model of flood propagation and recession in urban road networks
Chao Fan, Xiangqi Jiang, Ali Mostafavi
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 44
Flood Prediction Using Machine Learning Models
Miah Mohammad Asif Syeed, Maisha Farzana, Ishadie Namir, et al.
2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) (2022), pp. 1-6
Open Access | Times Cited: 23
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