Discriminant analysis of multivariate time series using wavelets [PDF]
In analyzing ECG data, the main aim is to differentiate between the signal patterns of those of healthy subjects and those of individuals with specific heart conditions.
M. Andrés Alonso, Ann Elizabeth Maharaj
core
Spectral Clustering of Precipitation Time Series in Golestan Province [PDF]
پژوهشنامه مدیریت حوزه آبخیزExtended Abstract Background: Clustering time series of precipitation and other hydrological elements by direct use of classic methods, such as K-means, can be misleading because there is a time-lagged correlation in time series observations that is ...
Nader Jandaghi +3 more
doaj
Clustering of financial time series
, 2013 This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models.
D'URSO, Pierpaolo +6 more
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Forecasting Time Series from Clusters. [PDF]
Forecasting large numbers of time series is a costly and time-consuming exercise. Before forecasting a large number of series that are logically connected in some way, the authors can first cluster them into groups of similar series.
Inder, B., Marahaj, E.A.
core
Zero-Inflated Time Series Clustering Via Ensemble Thick-Pen Transform. [PDF]
J Classif, 2023 Kim M, Oh HS, Lim Y.
europepmc +1 more source
KDiscShapeNet: A Structure-Aware Time Series Clustering Model with Supervised Contrastive Learning
MathematicsTime 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 +3 more
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Comparison of time series clustering methods for identifying novel subphenotypes of patients with infection. [PDF]
J Am Med Inform Assoc, 2023 Bhavani SV +8 more
europepmc +1 more source
Unfolding preprocessing for meaningful time series clustering.
, 2006 Clustering methods are commonly applied to time series, either as a preprocessing stage for other methods or in their own right. In this paper it is explained why time series clustering may sometimes be considered as meaningless.
Simon, Geoffroy +2 more
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Short-term exposure sequences and anxiety symptoms: a time series clustering of smartphone-based mobility trajectories. [PDF]
Int J Health Geogr, 2023 Lan Y, Helbich M.
europepmc +1 more source
Clustering distributed time series in sensor networks [PDF]
, 2008 Mohamed Medhat Gaber +3 more
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