Evaluation of Feature Selection Methods and Machine Learning Models for Identifying Collided Positions of Containers Equipped with an Accelerometer

Exploring foci of: Preprints.org Evaluation of Feature Selection Methods and Machine Learning Models for Identifying Collided Positions of Containers Equipped with an Accelerometer January 2025 • Xin Zhang, Zihan Song, Do-Myung Park, Byung-Kwon Park In the logistics and trade that are highly dependent on containers, efficient identification of col-lided positions is of great significance for enhancing cargo safety supervision and accident respon-sibility. Traditional methods that rely on visual inspections require a lot of manpower, are time-consuming and costly. This study proposes a machine learning-based system to identify col-lided positions using the data collected through accelerometers installed on container doors. This study also uses feature selectio… Open Article Page

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