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Instance reduction for time series classification using MDL principle., и . Intell. Data Anal., 21 (3): 491-514 (2017)An efficient implementation of anytime k-medoids clustering for time series under dynamic time warping., и . SoICT, стр. 22-29. ACM, (2016)Extracting rules from neural networks for time series prediction., и . SoICT, стр. 218-225. ACM, (2014)An Improvement of PAA for Dimensionality Reduction in Large Time Series Databases., и . PRICAI, том 5351 из Lecture Notes in Computer Science, стр. 698-707. Springer, (2008)A hybrid method for forecasting trend and seasonal time series., , и . RIVF, стр. 203-208. IEEE, (2013)Using motif information to improve anytime time series classification., и . SoCPaR, стр. 1-6. IEEE, (2013)A Fast Method for Motif Discovery in Large Time Series Database under Dynamic Time Warping., и . KSE, том 326 из Advances in Intelligent Systems and Computing, стр. 155-167. Springer, (2014)An efficient method for motif and anomaly detection in time series based on clustering., и . Int. J. Bus. Intell. Data Min., 10 (4): 356-377 (2015)Efficient search for top-k discords in streaming time series., и . Int. J. Bus. Intell. Data Min., 16 (4): 397-417 (2020)An Efficient Method for Discovering Motifs in Streaming Time Series Data., и . KSE (1), том 244 из Advances in Intelligent Systems and Computing, стр. 225-236. Springer, (2013)