讲座题目：飞机重着陆事件模式识别和预防—基于QAR数据的函数型数据分析

主 讲 人：华东师范大学方方教授

讲座时间：2023年12月13日（周三）15：00-16：00

讲座地点：6号学院楼402

主办单位：伟德BETVlCTOR1946源于英国、浙江省2011“数据科学与大数据分析协同创新中心”

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.

主讲人简介：

方方，华东师范大学统计学院教授，博士生导师。本科和博士先后毕业于北京大学数学系和美国威斯康星大学统计系。在2013年加入华东师范大学之前，曾在通用电气金融集团和上海浦东发展银行任职多年。主要研究方向为缺失数据、模型平均、碎片化数据分析、KS学习。在包括AOS/JOE/Biometrika在内的国际一流统计期刊上发表论文30余篇。先后主持和参与国家和省部级项目12项。目前主持国家自然科学基金重点项目“大数据背景下不完全数据的统计分析方法、理论和应用”。授权专利6项。曾获上海市自然科学二等奖。担任全国工业统计学教学研究会常务理事、中国现场统计研究会机器学习分会常务理事、数字经济与区块链技术分会副理事长，IMS China委员会委员，SCI期刊Journal of Nonparametric Statistics副主编。在应用领域长期关注信用评分和民航QAR大数据分析。出版统计科普小说《统计王国奇遇记》。

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