상하수도학회지 (Journal of Korean Society of Water and Wastewater)

  • 제34권6호
  • /
  • Pages.481-493
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  • 2020
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  • 1225-7672(pISSN)
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  • 2287-822X(eISSN)
대한상하수도학회 (The Korean Society of Water and Wastewater)
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수 환경 분야에서의 딥러닝 모델 적용사례

Deep learning model in water-environment field

  • 표종철 (울산과학기술원 도시환경공학부) ;
  • 박상훈 (울산과학기술원 도시환경공학부) ;
  • 조경화 (울산과학기술원 도시환경공학부) ;
  • 백상수 (울산과학기술원 도시환경공학부)
  • Pyo, Jongcheol (Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • Park, Sanghun (Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • Cho, Kyung-Hwa (Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • Baek, Sang-Soo (Urban and Environmental Engineering, Ulsan National Institute of Science and Technology)
  • 투고 : 2020.08.14
  • 심사 : 2020.11.18
  • 발행 : 2020.12.15
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초록

Deep learning models, which imitate the function of human brain, have drawn attention from many engineering fields (mechanical, agricultural, and computer engineering etc). The major advantages of deep learning in engineering fields can be summarized by objects detection, classification, and time-series prediction. As well, it has been applied into environmental science and engineering fields. Here, we compiled our previous attempts to apply deep learning models in water-environment field and presented the future opportunities.

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과제정보

이 논문은 정부(미래창조과학부)의 재원으로 한국연구재단의 지원을 받아 수행된 해양극지 기초 원천기술 개발 사업임 (NRF-2016M1A5A1027457)

참고문헌

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