JpGU Meeting 2021
Session Outline| Atmospheric and Hydrospheric Sciences (A) | ||||
|---|---|---|---|---|
| Session Sub-category | Complex & General (CG) | |||
| Session ID | A-CG43 | |||
| Title | Earth & Environmental Sciences and Artificial Intelligence/Machine Learning | |||
| Short Title | Earth & Environmental Sciences and AI/ML | |||
| Date & Time | Oral session | JUNE 3 (THU) PM1, PM2 | Channel | 07 (PM1), 06 (PM2) |
| Poster session | JUNE 3 (THU) PM3 | Main Convener | Name | Tomohiko Tomita |
| Affiliation | Faculty of Advanced Science and Technology, Kumamoto University | |||
| Co-Convener 1 | Name | Shigeki Hosoda | ||
| Affiliation | Japan Marine-Earth Science and Technology | |||
| Co-Convener 2 | Name | Ken-ichi Fukui | ||
| Affiliation | Osaka University | |||
| Co-Convener 3 | Name | Satoshi Ono | ||
| Affiliation | Kagoshima Univeristy | |||
| Session Language | J | |||
| Scope | In recent years, we have been required to explore various gigantic data leading earth and environmental sciences such as modern meteorology, oceanography, hydrology and so on to accomplish Society 5.0 and Sustainable Development Goals (SDGs). To examine such gigantic environmental data faithfully, it may be required to use the techniques of artificial intelligence/machine learning (AI/ML) including spatiotemporal data modeling of AI, prediction and detection by ML, techniques of automated data mining, and so forth. At the present, AI/ML is also expected to lead the data-driven science as a bridge connecting science and big data. This session calls for various studies applying the techniques of AI/ML to scientific/environmental issues and will discuss them in both natural and information sciences. | |||
| Presentation Format | Oral and Poster presentation | Collaboration | Joint with | - |
| Co-sponsored with | - | |||