Machine learning solutions in sewer systems: a bibliometric analysis
Author:
Affiliation:
1. Eurecat, Technology Centre of Catalonia, Unit of Applied Artificial Intelligence, Barcelona, Spain
2. Department of Computer Science and Industrial Engineering, University of Lleida, Lleida, Spain
Funder
European Union’s Horizon 2020 Research and Innovation Programme
Spanish Ministry of Science and Innovation
Agència de Gestió d’Ajuts Universitaris i de Recerca
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/1573062X.2022.2138460
Reference85 articles.
1. Is Google Scholar useful for bibliometrics? A webometric analysis
2. Bibliometric analysis of global scientific literature on effects of COVID-19 pandemic on mental health
3. Machine Learning Pipeline for Reusing Pretrained Models
4. Trends on Advanced Information and Communication Technologies for Improving Agricultural Productivities: A Bibliometric Analysis
5. Sewer solids—20 years of investigation
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