教師資料查詢 | 類別: 期刊論文 | 教師: 徐煥智SHYUR HUAN-JYH (瀏覽個人網頁)

標題:Using Deep Learning Approach in Flight Exceedance Event Analysis
學年110
學期1
出版(發表)日期2021/10/30
作品名稱Using Deep Learning Approach in Flight Exceedance Event Analysis
作品名稱(其他語言)
著者Huan-Jyh Shyur; Chi-Bin Cheng; Yu-Lin Hsiao
單位
出版者
著錄名稱、卷期、頁數Journal of Information Science and Engineering 37(6), p.1405-1418
摘要Causal analysis of flight exceedance events, e.g. hard-landing, is a key task for mod-ern 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 state-of-the-art techniques, the proposed approach provides a more reliable results. The technique can be the basis of de-veloping advanced models for further revealing the relationships between pilot operations and flight exceedance events.
關鍵字hard landing;quick access recorder;deep learning;BLSTM;RNN
語言英文(美國)
ISSN1016-2364
期刊性質國內
收錄於SCI;
產學合作
通訊作者Huan-Jyh Shyur
審稿制度
國別中華民國
公開徵稿
出版型式,電子版,紙本
相關連結
SDGs
  • 產業創新與基礎設施
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