인공지능을 활용한 지구과학 발전
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 허식 | - |
dc.contributor.author | 김진경 | - |
dc.date.accessioned | 2020-07-15T20:34:41Z | - |
dc.date.available | 2020-07-15T20:34:41Z | - |
dc.date.created | 2020-02-11 | - |
dc.date.issued | 2016-09-22 | - |
dc.identifier.uri | https://sciwatch.kiost.ac.kr/handle/2020.kiost/24606 | - |
dc.description.abstract | 지능정보 동향 / 인공지능이란? / 해외 동향 / 국내 동향 / 지구과학 분야에 대한 인공지능 추진 필요성 / Need to Analyze Disparate Data Sets at whole basin and single play resolution (Paradigm, 2016) / Multi-domains, Multi-disciplines Precess (Paradigm, 2016) / 인공지능 자원탐사 워크플로우 (Landmark, 2015) / The E&P Data Analysis workflow (Paradigm, 2016) / 해양 인공지능 flowchart / Artificial Intelligence Techniques in Reservoir Characterization: Functional networks softsensor for formation porosity and water saturation in oil Wells / Baic flow chart of seismic pattern recognition (multi-attribute analysis) / Classification / Approaches to image recognition / Hybrid attributes / Artificial intelligence is shaping the future of energy, but dont forget the risks / A Rube Goldberg View of a Hydrocarbon System / Dimensions of deep-seas hydrographical, biogeochemical & biogeographical provinces, and of organisms and their habitat - Deep-ocean Observing System by GOOS / Needs of Three Distinct Oceean Observing Communities for Understanding and Monitoring of Natural and Anthropogenic Earth Processes - (Deep-ocean Observing ystem by GOOS) / Science Challenges for Deep-ocean Observing System by GOOS / 이수부호의 특성: 태평양에서 인도양까지 동-서 방향 대양탐사 / 아라온호의 특성: 북극에서 남극까지 남-북 방향 극지탐사 / 무인 관측 장비 (심해 부이, ROV, AUV, ARGO, 글라이더, 로봇, 센서) / 무인 관측 장비 (해양 드론, 항해 드론, 무인 aradigm, 2016) / 인공지능 자원탐사 워크플로우 (Landmark, 2015) / The E&P Data Analysis workflow (Paradigm, 2016) / 해양 인공지능 flowchart / Artificial Intelligence Techniques in Reservoir Characterization: Functional networks softsensor for formation porosity and water saturation in oil Wells / Baic flow chart of seismic pattern recognition (multi-attribute analysis) / Classification / Approaches to image recognition / Hybrid attributes / Artificial intelligence is shaping the future of energy, but dont forget the risks / A Rube Goldberg View of a Hydrocarbon System / Dimensions of deep-seas hydrographical, biogeochemical & biogeographical provinces, and of organisms and their habitat - Deep-ocean Observing System by GOOS / Needs of Three Distinct Oceean Observing Communities for Understanding and Monitoring of Natural and Anthropogenic Earth Processes - (Deep-ocean Observing ystem by GOOS) / Science Challenges for Deep-ocean Observing System by GOOS / 이수부호의 특성: 태평양에서 인도양까지 동-서 방향 대양탐사 / 아라온호의 특성: 북극에서 남극까지 남-북 방향 극지탐사 / 무인 관측 장비 (심해 부이, ROV, AUV, ARGO, 글라이더, 로봇, 센서) / 무인 관측 장비 (해양 드론, 항해 드론, 무인 | - |
dc.description.uri | 2 | - |
dc.language | Korean | - |
dc.publisher | 한국지구과학회 | - |
dc.relation.isPartOf | 2016 한국지구과학회 추계학술발표회 | - |
dc.title | 인공지능을 활용한 지구과학 발전 | - |
dc.title.alternative | Advancement of Geosciences through Artificial Intelligence | - |
dc.type | Conference | - |
dc.citation.conferencePlace | KO | - |
dc.citation.endPage | 19 | - |
dc.citation.startPage | 3 | - |
dc.citation.title | 2016 한국지구과학회 추계학술발표회 | - |
dc.contributor.alternativeName | 허식 | - |
dc.identifier.bibliographicCitation | 2016 한국지구과학회 추계학술발표회, pp.3 - 19 | - |
dc.description.journalClass | 2 | - |