講座題目：飛機重著陸事件模式識別和預防—基于QAR數據的函數型數據分析
主 講 人：華東師范大學方方教授
講座時間：2023年12月13日（周三）15：00-16：00
講座地點：6號學院樓402
主辦單位：新葡萄8883官網AMG、浙江省2011“數據科學與大數據分析協同創新中心”
摘要：
Hard landing is one of the most common safety events in the aviation industry, which has been a critical concern of airlines and aviation administration for a long time. Although the analysis of Quick Access Recorder (QAR) data has the potential to illuminate the formation reason of a hard landingevent, most existing methodologies overlook the curve characteristics of QAR parameters and focus on a straightforward prediction problem for hard landing. These methods usually lack interpretability and provide limited preventative insights. This paper presents the Hard Landing Pattern Recognition andPrecaution Pipeline (HL3P), an innovative framework designed to recognize different landing patterns of flights and provide proactive suggestions against hard landing. Utilizing functional data analysis techniques, we first identify the key QAR parameters that have critical impacts on hard landing and subsequently recognize distinctive landing patterns that exhibit noticeable disparities. Through a detailed comparison of landing curves and pilot operations between normal and hard landing flights,we provide insights into the formation reason for hard landing and offer practicable landing advice for pilots.
主講人簡介：
方方，華東師范大學統計學院教授，博士生導師。本科和博士先后畢業于北京大學數學系和美國威斯康星大學統計系。在2013年加入華東師范大學之前，曾在通用電氣金融集團和上海浦東發展銀行任職多年。主要研究方向為缺失數據、模型平均、碎片化數據分析、KS學習。在包括AOS/JOE/Biometrika在內的國際一流統計期刊上發表論文30余篇。先后主持和參與國家和省部級項目12項。目前主持國家自然科學基金重點項目“大數據背景下不完全數據的統計分析方法、理論和應用”。授權專利6項。曾獲上海市自然科學二等獎。擔任全國工業統計學教學研究會常務理事、中國現場統計研究會機器學習分會常務理事、數字經濟與區塊鏈技術分會副理事長，IMS China委員會委員，SCI期刊Journal of Nonparametric Statistics副主編。在應用領域長期關注信用評分和民航QAR大數據分析。出版統計科普小說《統計王國奇遇記》。
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