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Cluster analysis of respiratory time series
Biological Cybernetics, 1978We have investigated the respiratory control system with the hypothesis that, although many variables such as minute ventilation (VI), tidal volume (VT), breathing period (TT), inspiratory duration (TI), and expiratory duration (TE) may be observed, the controller functions more simply by manipulating only 2 or 3 of these.
J M, Adams, E O, Attinger, F M, Attinger
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Tiered Clustering for Time Series Data
2021Clustering is an essential unsupervised learning method. While the clustering of discrete data is a reasonably solved problem, sequential data clustering, namely time series data, is still an ongoing problem. Sequential data such as time series is widely used due to its abundance of detailed information.
Ruizhe Ma, Rafal A. Angryk
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Evolutionary Hierarchical Time Series Clustering
Sixth International Conference on Intelligent Systems Design and Applications, 2006Time series clustering is an important topic, particularly for similarity search amongst long time series such as those arising in bioinformatics. In this paper a new evolutionary algorithm for detecting the hierarchical structure of an input time series data set is proposed.
Monica Chis, Crina Grosan
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MDL-based time series clustering
Knowledge and Information Systems, 2012Time series data are pervasive across all human endeavors, and clustering is arguably the most fundamental data mining application. Given this, it is somewhat surprising that the problem of time series clustering from a single stream remains largely unsolved.
Thanawin Rakthanmanon +3 more
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A Clustering Algorithm for Time Series Data
2006 Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'06), 2006In the Intelligent Traffic System, the research about the analysis of time series of traffic flow is important and meaningful. Using clustering methods to analyze time series not only can find some typical patterns of traffic flow, but also can group the sections of highway by their different flow characteristics.
Jian Yin 0001 +2 more
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Clustering Random Walk Time Series
2015We present in this paper a novel non-parametric approach useful for clustering independent identically distributed stochastic processes. We introduce a pre-processing step consisting in mapping multivariate independent and identically distributed samples from random variables to a generic non-parametric representation which factorizes dependency and ...
Gautier Marti +3 more
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Convex Clustering for Autocorrelated Time Series
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Max Revay, Victor Solo
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Clustering of time series with genetic algorithms.
1999presentato al Convegno SCO99 Venezia ...
BARAGONA, Roberto +2 more
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Time-Series Clustering Based on the Characterization of Segment Typologies
IEEE Transactions on Cybernetics, 2021David Guijo-Rubio +2 more
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