Univariate and multivariate time series classification with parametric integral dynamic time warping
暂无分享,去创建一个
[1] Mu-Yen Chen,et al. Online fuzzy time series analysis based on entropy discretization and a Fast Fourier Transform , 2014, Appl. Soft Comput..
[2] Han Liu,et al. Rule-based systems: a granular computing perspective , 2016, Granular Computing.
[3] Ying Wah Teh,et al. Time-series clustering - A decade review , 2015, Inf. Syst..
[4] Tomasz Górecki,et al. First and Second Derivatives in Time Series Classification Using DTW , 2014, Commun. Stat. Simul. Comput..
[5] Jun Wang,et al. On the Non-Trivial Generalization of Dynamic Time Warping to the Multi-Dimensional Case , 2015, SDM.
[6] Jian Pei,et al. A brief survey on sequence classification , 2010, SKDD.
[7] George E. P. Box,et al. Time Series Analysis: Box/Time Series Analysis , 2008 .
[8] Hui Ding,et al. Querying and mining of time series data: experimental comparison of representations and distance measures , 2008, Proc. VLDB Endow..
[9] Mu-Yen Chen,et al. A high-order fuzzy time series forecasting model for internet stock trading , 2014, Future Gener. Comput. Syst..
[10] G. Pfurtscheller,et al. Brain–Computer Communication: Motivation, Aim, and Impact of Exploring a Virtual Apartment , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[11] Maciej Łuczak,et al. Hierarchical clustering of time series data with parametric derivative dynamic time warping , 2016 .
[12] Daniel Lemire,et al. Faster retrieval with a two-pass dynamic-time-warping lower bound , 2008, Pattern Recognit..
[13] Eamonn J. Keogh,et al. On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration , 2002, Data Mining and Knowledge Discovery.
[14] T. Warren Liao,et al. Clustering of time series data - a survey , 2005, Pattern Recognit..
[15] Mu-Yen Chen,et al. A hybrid fuzzy time series model based on granular computing for stock price forecasting , 2015, Inf. Sci..
[16] Geoffrey I. Webb,et al. Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm , 2015, Knowledge and Information Systems.
[17] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[18] Tomasz Górecki,et al. Non-isometric transforms in time series classification using DTW , 2014, Knowl. Based Syst..
[19] Donald J. Berndt,et al. Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.
[20] Tomasz Górecki,et al. Multivariate time series classification with parametric derivative dynamic time warping , 2015, Expert Syst. Appl..
[21] Eamonn Keogh. Exact Indexing of Dynamic Time Warping , 2002, VLDB.
[22] Witold Pedrycz,et al. The development of granular rule-based systems: a study in structural model compression , 2017, GRC 2017.
[23] Georg Peters,et al. DCC: a framework for dynamic granular clustering , 2016 .
[24] Xuesong Zhou,et al. Method for investigating intradriver heterogeneity using vehicle trajectory data: A Dynamic Time Warping approach , 2015 .
[25] Yiyu Yao. A triarchic theory of granular computing , 2016 .
[26] Tomasz Górecki,et al. Using derivatives in time series classification , 2012, Data Mining and Knowledge Discovery.
[27] Andrzej Skowron,et al. Interactive granular computing , 2016 .