期刊論文
| 學年 | 108 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2020-07-01 |
| 作品名稱 | Using deep learning approach in flight exceedance event analysis |
| 作品名稱（其他語言） | |
| 著者 | H.-J. Shyur; C.-B. Cheng; Y. Hsiao |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Journal of Information Science and Engineering, 37, 1405-1418. |
| 摘要 | Causal analysis of flight exceedance events, e.g. hard-landing, is a key task for modern airlines performing Flight Operation Quality Assurance (FOQA) programs. The main objective of the program is to learn from experience: detect early signs of major problems and correct them before accidents occur. It has been found that flare operation would greatly influence the landing performance. According to the finding, we proposed a deep learning approach to assist airlines performing causal analysis for hard landing events. Experimental results confirm that compared with the other stateof-the-art techniques, the proposed approach provides a more reliable results. The technique can be the basis of developing advanced models for further revealing the relationships between pilot operations and flight exceedance events. |
| 關鍵字 | |
| 語言 | en_US |
| ISSN | |
| 期刊性質 | 國外 |
| 收錄於 | SCI Scopus |
| 產學合作 | 國內 |
| 通訊作者 | H.-J. Shyur |
| 審稿制度 | 是 |
| 國別 | TWN |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/119988 ) |