doi: 10.7469/JKSQM.2019.47.3.497


Long Short-Term Memory를 활용한 건화물운임지수 예측

Prediction of Baltic Dry Index by Applications of Long Short-Term Memory

  • HAN,Minsoo(한국해양대학교 대학원 해운경영학과),
  • YU,Song-Jin(한국해양대학교 해운경영학부)

피인용문헌(Cited by)

  • . "A Baltic Dry Index Prediction using Deep Learning Models" Journal of Korea trade, vol. 25(4), p.17-. 2021. doi:10.35611/jkt.2021.25.4.17
  • . "Attention 기반 Encoder-Decoder 모델을 활용한작물의 생산량 예측" 品質經營學會誌, vol. 49(4), p.569-. 2021. doi:10.7469/JKSQM.2021.49.4.569
  • . "A Study on the Forecasting of Bunker Price Using Recurrent Neural Network" 韓國컴퓨터情報學會論文誌, vol. 26(10), p.179-. 2021. doi:10.9708/jksci.2021.26.10.179
  • . "Forecasting LNG Freight rate with Artificial Neural Networks" 韓國컴퓨터情報學會論文誌, vol. 27(7), p.187-. 2022. doi:10.9708/jksci.2022.27.07.187