지속가능 물관리를 위한 ESG와 인공지능

  • Published : 2021.07.30

Abstract

Keywords

References

  1. 김성훈 (2021), "K-water AI 연구소운영 및 가상센서 기술개발", K-water AI-빅데이터 포럼.
  2. 김수현, 김창훈 (2020), "유럽 그린딜의 동향과 시사점", 에너지경제연구원.
  3. 박노혁 (2021), "디지털로 바라보는 바람직한 물재해 관리상", 대한토목학회지.
  4. 삼정KPMG 경제연구원 (2020), "ESG 경영시대, 전략 패러다임 대전환", 삼정KPMG.
  5. 신민영 (2021), "ESG경영과 경제 패러다임의 대전환", ESG경제.
  6. 정환보 (2021), "ESG에서도 으뜸은 E(환경)...", 경향비즈.
  7. Ahmed, H. O. Dennis Wong, M. L, and Nandi. A. K., (2018). "Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse overcomplete features," Mechanical Systems and Signal Processing Vol.9, pp. 459-477.
  8. EU Ministerial Declartion (2021), "A Green and Digital Transformation of the EU." Digital Day 2021.
  9. Hinton, G. E., and Zemel, R. S. (1994). "Autoencoders, minimum description length and helmholtz free energy." In Advances in Neural Information Processing Systems Vol.5, pp. 3-10.
  10. Laura von Ruedel, et. al. (2020), "Combining machine learning and simulation to a hybrid modelling approach: current and future directions.", International Symposium on Intelligent Data Analysis (IDA) Conference.
  11. Microsystems Technology Office, (2017), "Lifelong Learning Machines (L2M)", Defense Advanced Research Projects Agency.
  12. http://www.waterjournal.co.kr/news/articleView.html?idxno=40064