Results 31 to 40 of about 751,199 (239)

KDiscShapeNet: A Structure-Aware Time Series Clustering Model with Supervised Contrastive Learning

Mathematics
Time series clustering plays a vital role in various analytical and pattern recognition tasks by partitioning structurally similar sequences into semantically coherent groups, thereby facilitating downstream analysis.
Xi Chen, Yufan Jiang, Yingming Zhang, Chunhe Song   +3 more
doaj   +1 more source

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
doaj   +1 more source

Power system transient security assessment based on multi-channel time series data mining

Energy Reports, 2022
In the context of the clean energy revolution and the high penetration of renewables and power electronics, data-driven Transient Security Assessment (TSA) models can significantly reduce the computational burden of power system TSA and adapt to the ...
Kangkang Wang, Han Diao, Wei Wei, Tannan Xiao, Ying Chen, Bo Zhou   +5 more
doaj   +1 more source

Interpretable Categorization of Heterogeneous Time Series Data [PDF]

, 2018
Understanding heterogeneous multivariate time series data is important in many applications ranging from smart homes to aviation. Learning models of heterogeneous multivariate time series that are also human-interpretable is challenging and not ...
Kochenderfer, Mykel J., Lee, Ritchie, Mengshoel, Ole J., Silbermann, Joshua   +3 more
core   +3 more sources

Survey on Feature Representation and Similarity Measurement of Time Series

Jisuanji kexue yu tansuo, 2021
Time series is a group of random numbers which are composed of the values of the same index according to the time sequence. With the rapid development of science and technology, the application of time series in the field of data mining becomes more and ...
SUN Dongpu, QU Li
doaj   +1 more source

Optimizing Dynamic Time Warping’s Window Width for Time Series Data Mining Applications [PDF]

, 2018
Dynamic Time Warping (DTW) is a highly competitive distance measure for most time series data mining problems. Obtaining the best performance from DTW requires setting its only parameter, the maximum amount of warping (w).
Bagnall, Anthony, Dau, Hoang Anh, Forestier, Germain, Keogh, Eamonn, Mueen, Abdullah, Petitjean, Francois, Silva, Diego Furtado   +6 more
core   +4 more sources

A Recent-Pattern Biased Dimension-Reduction Framework for Time Series Data

Journal of Advances in Information Technology, 2010
High-dimensional time series data need dimension-reduction strategies to improve the efficiency of computation and indexing. In this paper, we present a dimension-reduction framework for time series.
Santi Phithakkitnukoon, Carlo Ratti
doaj   +1 more source

A Better Alternative to Piecewise Linear Time Series Segmentation [PDF]

, 2005
Time series are difficult to monitor, summarize and predict. Segmentation organizes time series into few intervals having uniform characteristics (flatness, linearity, modality, monotonicity and so on).
Lemire, Daniel
core   +8 more sources

Time Series Optimization on Data Mining

Journal of Physics: Conference Series, 2019
Abstract Forecasting is one of the important topics in the data mining field, such as, predictions, weather forecasting, predictions of academic achievement. Another topic associated with forecasting through a series of data that depends on the time period is called time series.
Relita Buaton, Herman Mawengkang, Muhammad Zarlis, Syahril Effendi, Akim Manaor Hara Pardede, Yani Maulita, Achmad Fauzi, N Novriyenni   +7 more
openaire   +1 more source

Flood prediction with time series data mining: Systematic review

Natural Hazards Research
The global community is continuously working to minimize the impact of disasters through various actions, including earth surveying. For example, flood-prone areas must be identified appropriately, predicted, understood, and socialized.
Dimara Kusuma Hakim, Rahmat Gernowo, Anang Widhi Nirwansyah   +2 more
doaj   +1 more source