Chaerim Park

2025

1. JKIIS

   1D-CNN-based wind prediction for marine accident response

   Chaerim Park ,  Do-Youn Kim ,  Yong-Hyuk Kim ,  and  Seung-Hyun Moon

   Journal of Korean Institute of Intelligent Systems, 2025
2. GECCO

   A Genetic Ensemble Method for Correcting Maritime Wind Forecasts

   Chaerim Park ,  Tae-Hoon Kim ,  Yong-Hyuk Kim ,  and  Seung-Hyun Moon

   In Proceedings of the Genetic and Evolutionary Computation Conference Companion , 2025

   Abs

   Maritime accidents can cause significant damage to both human life and the environment. To respond quickly and effectively, accurate wind prediction is crucial. This study focuses on optimizing the weights of an ensemble voting model for wind data prediction using genetic algorithms (GAs). The GA-based approach significantly improved wind prediction accuracy by optimizing the weights of various models. Data from seven observation stations near South Korea was used, and the GA-based model outperformed the ECMWF High-Resolution model, achieving a 24.6% improvement in RMSE. This highlights the potential of GA in wind prediction models and its significant application in maritime accident response systems.

3. JKIIS

   Comparative Analysis of Fine-Tuning and Retrieval-Augmented Generation Approaches for Artwork Question Answering

   Jung-Muk Hwang ,  Chaerim Park ,  and  Seung-Hyun Moon

   Journal of Korean Institute of Intelligent Systems, 2025