| タイトル | Automated Data Assimilation and Flight Planning for Multi-Platform Observation Missions |
| 本文（外部サイト） | http://hdl.handle.net/2060/20090026327 |
| 著者（英） | Morris, Robert A.; Kurklu, Elif; Strawa, Anthony; Keely, Leslie; Oza, Nikunj |
| 著者所属（英） | NASA Ames Research Center |
| 発行日 | 2008-08-24 |
| 言語 | eng |
| 内容記述 | This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced techniques are currently being integrated into daily mission operations. Consequently, there are significant gaps in the knowledge that can be derived from the models and data that are used each day for guiding mission activities. The result can be sub-optimal observation plans, lack of useful data, and wasteful use of resources. Recent advances in data mining, machine learning, and planning make it feasible to migrate these technologies into the daily mission planning cycle. We describe the design of a closed loop system for data acquisition, processing, and flight planning that integrates the results of machine learning into the flight planning process. |
| NASA分類 | Documentation and Information Science |
| レポートNO | ARC-E-DAA-TN-132 |
| 権利 | Copyright, Distribution as joint owner in the copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/253281 |
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