@article{ART003329436},
author={Jaehee Lee and Junhyuk Park and Seungyong Seong and Chaeeun Seo and Hyo-Beom Ahn},
title={A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2026},
volume={31},
number={4},
pages={11-22}
TY - JOUR
AU - Jaehee Lee
AU - Junhyuk Park
AU - Seungyong Seong
AU - Chaeeun Seo
AU - Hyo-Beom Ahn
TI - A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction
JO - Journal of The Korea Society of Computer and Information
PY - 2026
VL - 31
IS - 4
PB - The Korean Society Of Computer And Information
SP - 11
EP - 22
SN - 1598-849X
AB - Red tide outbreaks cause severe damage to marine ecosystems, necessitating robust early warning systems. However, traditional models based on single data sources struggle with the nonlinear complexity of environmental factors. This study proposes a multimodal prediction model integrating GOCI satellite imagery and oceanographic numerical data. By combining spatial-temporal satellite features with time-series environmental variables, the model predicts red tide occurrences across 31 Korean coastal regions. The proposed model achieved a Precision of 0.64, Recall of 0.82, and F1-score of 0.72, significantly outperforming existing LSTM-based methods (F1-score = 0.574). These results demonstrate the potential of multimodal integration for real-time red tide forecasting and decision support.
KW - Multimodal Artificial Intelligence;Red Tide;Deep Learning;LSTM;Cross Attention;Multi-Head Learning
DO -
UR -
ER -
Jaehee Lee, Junhyuk Park, Seungyong Seong, Chaeeun Seo and Hyo-Beom Ahn. (2026). A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction. Journal of The Korea Society of Computer and Information, 31(4), 11-22.
Jaehee Lee, Junhyuk Park, Seungyong Seong, Chaeeun Seo and Hyo-Beom Ahn. 2026, "A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction", Journal of The Korea Society of Computer and Information, vol.31, no.4 pp.11-22.
Jaehee Lee, Junhyuk Park, Seungyong Seong, Chaeeun Seo, Hyo-Beom Ahn "A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction" Journal of The Korea Society of Computer and Information 31.4 pp.11-22 (2026) : 11.
Jaehee Lee, Junhyuk Park, Seungyong Seong, Chaeeun Seo, Hyo-Beom Ahn. A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction. 2026; 31(4), 11-22.
Jaehee Lee, Junhyuk Park, Seungyong Seong, Chaeeun Seo and Hyo-Beom Ahn. "A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction" Journal of The Korea Society of Computer and Information 31, no.4 (2026) : 11-22.
Jaehee Lee; Junhyuk Park; Seungyong Seong; Chaeeun Seo; Hyo-Beom Ahn. A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction. Journal of The Korea Society of Computer and Information, 31(4), 11-22.
Jaehee Lee; Junhyuk Park; Seungyong Seong; Chaeeun Seo; Hyo-Beom Ahn. A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction. Journal of The Korea Society of Computer and Information. 2026; 31(4) 11-22.
Jaehee Lee, Junhyuk Park, Seungyong Seong, Chaeeun Seo, Hyo-Beom Ahn. A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction. 2026; 31(4), 11-22.
Jaehee Lee, Junhyuk Park, Seungyong Seong, Chaeeun Seo and Hyo-Beom Ahn. "A Study on the Analysis and Improvement of Artificial Intelligence Based Multimodal Red Tide Prediction" Journal of The Korea Society of Computer and Information 31, no.4 (2026) : 11-22.
