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时间序列特征提取方法研究综述
引用本文:任守纲,张景旭,顾兴健,熊迎军,王浩云,徐焕良.时间序列特征提取方法研究综述[J].小型微型计算机系统,2021(2):271-278.
作者姓名:任守纲  张景旭  顾兴健  熊迎军  王浩云  徐焕良
作者单位:南京农业大学信息科技学院;国家信息农业工程技术中心;江苏省物联网技术与应用协同创新中心
基金项目:国家自然科学基金青年项目(61806097)资助;国家重点研发计划项目(2018YFD0501900)资助.
摘    要:随着物联网、大数据和人工智能等技术研究和应用的蓬勃发展,各类时间序列数据不断涌现.时间序列数据特征是表象,内在蕴含着丰富的领域知识,如何高效分析时间序列特征模式,提取可辨识的时间序列特征,挖掘数据蕴含的规律,正成为业界研究的热点.本文首先介绍时间序列概念,综述了时间序列分类、聚类和预测三方面研究的最新进展;然后从时间序...

关 键 词:时间序列  数据挖掘  特征提取  机器学习

Overview of Feature Extraction Algorithms for Time Series
REN Shou-gang,ZHANG Jing-xu,GU Xing-jian,XIONG Ying-jun,WANG Hao-yun,XU Huan-liang.Overview of Feature Extraction Algorithms for Time Series[J].Mini-micro Systems,2021(2):271-278.
Authors:REN Shou-gang  ZHANG Jing-xu  GU Xing-jian  XIONG Ying-jun  WANG Hao-yun  XU Huan-liang
Affiliation:(College of Information Science and Technology,Nanjing 210095,China;Nanjing Agricultural University National Engineering and Technology Center for Infomation Agriculture,Nanjing 210095,China;Jiangsu Collaborative Center for the Technology and Application of Internet of Things,Nanjing 210023,China)
Abstract:With the development of machine learning,new technologies continue to emerge in the field of time-series.How to efficiently analyze the internal patterns of time series and extract the identifiable characteristics of time series is becoming a research hotspot.This article first introduces the latest developments in TS research,then analyze and compare the research situation of machine learning methods on time series in detail from the aspects of waveform extraction,time-dependent characteristics,and sequence transformation of the feature extraction algorithm,and finally based on the development trend of the current time series feature extraction algorithm,the future development of the time series feature extraction algorithm is prospected.
Keywords:time series  data mining  feature extraction  machine learning
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