Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions.
Sign Up to like & getrecommendations! Published in 2021 at "ISA transactions"
DOI: 10.1016/j.isatra.2021.02.042
Abstract: The research on intelligent fault diagnosis has yielded remarkable achievements based on artificial intelligence-related technologies. In engineering scenarios, machines usually work in a normal condition, which means limited fault data can be collected. Intelligent fault… read more here.
Keywords: fault; imbalanced data; research; diagnosis ... See more keywords
CSIML: a cost-sensitive and iterative machine-learning method for small and imbalanced materials data sets
Sign Up to like & getrecommendations! Published in 2024 at "Chemistry Letters"
DOI: 10.1093/chemle/upae090
Abstract: Materials science research benefits from the powerful machine-learning (ML) surrogate models, but it is also limited by the implicit requirement for sufficiently big and balanced data distribution for ML. In this paper, we propose a… read more here.
Keywords: materials data; data sets; small imbalanced; machine learning ... See more keywords