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Generalized relational tensors for chaotic time series [PDF]
PeerJ Computer Science, 2023 The article deals with a generalized relational tensor, a novel discrete structure to store information about a time series, and algorithms (1) to fill the structure, (2) to generate a time series from the structure, and (3) to predict a time series. The
Vasilii A. Gromov +2 more
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Space-efficient representations of raster time series
Information Sciences, 2021 Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG [Abstract] Raster time series, a.k.a. temporal rasters, are collections of rasters covering the same region at consecutive timestamps. These data have been used in many different applications ranging from weather forecast systems to monitoring of forest degradation or soil ...
Silva-Coira, Fernando +3 more
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Transitional SAX Representation for Knowledge Discovery for Time Series
Applied Sciences, 2020 Numerous dimensionality-reducing representations of time series have been proposed in data mining and have proved to be useful, especially in handling a high volume of time series data.
Kiburm Song, Minho Ryu, Kichun Lee
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Hexadecimal Aggregate Approximation Representation and Classification of Time Series Data
Algorithms, 2021 Time series data are widely found in finance, health, environmental, social, mobile and other fields. A large amount of time series data has been produced due to the general use of smartphones, various sensors, RFID and other internet devices. How a time
Zhenwen He +3 more
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Optimizing Functional Network Representation of Multivariate Time Series [PDF]
Scientific Reports, 2012 By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper ...
Zanin, Massimiliano +7 more
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LBP4MTS: Local Binary Pattern-Based Unsupervised Representation Learning of Multivariate Time Series
IEEE Access, 2023 Representation learning of multivariate time series is a crucial and complex task that offers valuable insights for numerous applications, including time series classification, trend analysis, and regression.
Chengyang Ye, Qiang Ma
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Time Series Piecewise Linear Representation Method Based on First-order Filtering [PDF]
Jisuanji gongcheng, 2016 For the time series whose slope fluctuation frequency is relatively fierce,time series piecewise algorithm with edge point extraction based on slope is easy to fall into local optimum.It cannot keep the overall features of original time series.For this ...
LIN Yi,WANG Zhibo
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Variable-Size Segmentation for Time Series Representation
, 2023 Given the high data volumes in time series applications, or simply the need for fast response times, it is usually necessary to rely on alternative, shorter representations of time series, usually with information loss. This incurs approximate comparisons of time series where precision is a major issue.
Djebour, Lamia +2 more
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Abridged Symbolic Representation of Time Series for Clustering
Acta Universitatis Lodziensis. Folia Oeconomica, 2019 In recent years a couple of methods aimed at time series symbolic representation have been introduced or developed. This activity is mainly justified by practical considerations such memory savings or fast data base searching.
Jerzy Korzeniewski
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Piecewise Trend Approximation: A Ratio-Based Time Series Representation
Abstract and Applied Analysis, 2013 A time series representation, piecewise trend approximation (PTA), is proposed to improve efficiency of time series data mining in high dimensional large databases.
Jingpei Dan +3 more
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