Neural Networks and Imbalanced Learning for Data-Driven Scientific Computing With Uncertainties
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3052680
Abstract: Uncertainty quantification in complex engineering problems is challenging because of necessitating large numbers of expensive model evaluations. This paper proposes a two-stage framework for developing accurate machine learning-based surrogate models in structural engineering. The studied… read more here.
Keywords: data driven; imbalanced learning; networks imbalanced; neural networks ... See more keywords
A Systematic Review on Imbalanced Learning Methods in Intelligent Fault Diagnosis
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3246470
Abstract: The theoretical developments of data -driven fault diagnosis methods have yielded fruitful achievements and significantly benefited industry practices. However, most methods are developed based on the assumption of data balance, which is incompatible with engineering… read more here.
Keywords: fault diagnosis; imbalanced learning; diagnosis; imbalance ... See more keywords
A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Software Engineering"
DOI: 10.1109/tse.2018.2836442
Abstract: Context: Software defect prediction (SDP) is an important challenge in the field of software engineering, hence much research work has been conducted, most notably through the use of machine learning algorithms. However, class-imbalance typified by… read more here.
Keywords: imbalance; imbalanced learning; mml; math ... See more keywords