Addressing data imbalance in collision risk prediction with active generative oversampling

Abstract Data imbalance is a critical factor affecting the predictive accuracy in collision risk assessment. This study proposes an advanced active generative oversampling method based on Query by Committee (QBC) and Auxiliary Classifier Generative Adversarial Network (ACGAN), integrated with the Wa...

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Bibliographic Details
Main Authors: Li Li, Xiaoliang Zhang
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-93851-3
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