Results 141 to 150 of about 303,598 (207)

Time series clustering and characterisation

In today’s data-driven society, the volume of time series data generated every second is enormous and is applied in various domains - from financial markets and sales forecasting and public health surveillance systems.
Poh, Isaac Zi Jie
core  

Multivariate time series clustering analysis of the Global Dietary Database to uncover patterns in dietary trends (1990-2018). [PDF]

Public Health Nutr
Matousek A, Leung TH, Pang H.
europepmc   +1 more source

Discovery of generalizable TBI phenotypes using multivariate time-series clustering. [PDF]

Comput Biol Med
Ghaderi H, Foreman B, Reddy CK, Subbian V.   +3 more
europepmc   +1 more source

Mathematical modelling and time series clustering of Mpox outbreak: A comparative study of the top 10 affected countries and implications for future outbreak management. [PDF]

Glob Epidemiol
Tamakloe MD, Kuuwill A, Osumanu I, Siripi H.   +3 more
europepmc   +1 more source

Corrigendum to 'Mathematical modelling and time series clustering of Mpox outbreak: A comparative study of the top 10 affected countries and implications for future outbreak management' [Global Epidemiology 10 (2025) 100214]. [PDF]

Glob Epidemiol
Tamakloe MD, Kuuwill A, Osumanu I, Siripi H.   +3 more
europepmc   +1 more source

A dynamic customer segmentation approach by combining LRFMS and multivariate time series clustering. [PDF]

Sci Rep
Wang S, Sun L, Yu Y.
europepmc   +1 more source

Time series clustering and characterization

Among the vast volumes of data generated daily in our modern digital world, time series data represents a major category with broad applicability. Time series data refers to a collection of data points indexed by time, and it has major practical uses in ...
Lie, Rhys
core  

Nanomechanical mass measurements through feature-based time series clustering. [PDF]

Rev Sci Instrum
Neumann AP, Gomez A, Nunn AR, Sader JE, Roukes ML.   +4 more
europepmc   +1 more source

Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study. [PDF]

JMIR Form Res
Yoo IJ, Park DH, Lee OE, Park A.
europepmc   +1 more source

Predicting CKD progression using time-series clustering and light gradient boosting machines. [PDF]

Sci Rep
Saito H, Yoshimura H, Tanaka K, Kimura H, Watanabe K, Tsubokura M, Ejiri H, Zhao T, Ozaki A, Kazama S, Shimabukuro M, Asahi K, Watanabe T, Kazama JJ.   +13 more
europepmc   +1 more source