计算机应用与软件2018，Vol.35Issue(1)：85-91,7.DOI:10.3969/j.issn.1000-386x.2018.01.014
聚类HMM模型在QAR数据分析中的应用研究
THE APPLICATION OF CLUSTERING HMM MODEL IN QAR DATA ANALYSIS
摘要
Abstract
QAR data is the streaming data obtained from the sensor during the flight.Facing with the huge QAR data,a clustering-based HMM model is proposed.According to the characteristics of QAR data,the changing characteristics of different attributes of QAR data during malfunction or abnormality are analysed and the main impacted attributes are extracted.The state trend of the data is obtained from the data discretization of its clustering,which means,the cluster is divided into multiple state trends and the HMM model is constructed during malfunction or abnormality which the malfunction or abnormality is described in the form of status switch.Also,the HMM model of related QAR data of air jolt is constructed to verify the effectiveness of the proposed model with the example of aircraft malfunction in air jolt.关键词
QAR数据/聚类/HMM模型/空中颠簸/状态趋势Key words
QAR data/Clustering/HMM model/Air jolt/State trend分类
信息技术与安全科学引用本文复制引用
杨慧,毛好好,霍纬纲..聚类HMM模型在QAR数据分析中的应用研究[J].计算机应用与软件,2018,35(1):85-91,7.基金项目
国家自然科学基金与中国民航联合基金项目(61179063) （61179063）
国家自然科学基金项目(61301245). （61301245）
