Machine Learning for Modeling Service Life: Comprehensive Review, Bibliometrics Analysis and Taxonomy
Author:
Affiliation:
1. Bánki Donát Faculty of Mechanical and Safety Engineering,Budapest,Hungary
2. John von Neumann Faculty of Informatics,Budapest,Hungary
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10297583/10297621/10297884.pdf?arnumber=10297884
Reference44 articles.
1. Statistics and Artificial Intelligence-Based Pavement Performance and Remaining Service Life Prediction Models for Flexible and Composite Pavement Systems
2. Tensile property prediction by feature engineering guided machine learning in reduced activation ferritic/martensitic steels
3. Service life prediction of fly ash concrete using an artificial neural network
4. Model-based data integration along the product & service life cycle supported by digital twinning
5. Evaluation of data-driven models for predicting the service life of concrete sewer pipes subjected to corrosion
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