Results 21 to 30 of about 227,005 (260)

INGARCH-based fuzzy clustering of count time series with a football application

Machine Learning with Applications, 2022
Although there are many contributions in the time series clustering literature, few studies still deal with count time series data. This paper aims to develop a fuzzy clustering procedure for count time series data.
Roy Cerqueti, Pierpaolo D’Urso, Livia De Giovanni, Raffaele Mattera, Vincenzina Vitale   +4 more
doaj   +1 more source

Clustering time series applied to energy markets

Energy Informatics, 2019
In Germany and many other countries the energy market has been subject to significant changes. Instead of only a few large-scale producers that serve aggregated consumers, a shift towards regenerative energy sources is taking place.
Cornelia Krome, Jan Höft, Volker Sander
doaj   +1 more source

Time series clustering in large data sets

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2011
The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM) with the unsupervised learning algorithm for clustering of time series.
Jiří Fejfar, Jiří Šťastný
doaj   +1 more source

Topic Network Analysis Based on Co-Occurrence Time Series Clustering

Mathematics, 2022
Traditional topic research divides similar topics into the same cluster according to clustering or classification from the perspective of users, which ignores the deep relationship within and between topics. In this paper, topic analysis is achieved from
Weibin Lin, Xianli Wu, Zhengwei Wang, Xiaoji Wan, Hailin Li   +4 more
doaj   +1 more source

Review of Multivariate Time Series Clustering Algorithms [PDF]

Jisuanji kexue yu tansuo
Multivariate time series (MTS) data, serving as a crucial basis for intelligent technologies across numerous domains, record the state changes of multiple variables in systems over time.
ZHENG Desheng, SUN Hanming, WANG Liyuan, DUAN Yaoxin, LI Xiaoyu
doaj   +1 more source

Equivalence partition based morphological similarity clustering for large-scale time series

Scientific Reports, 2023
Data clustering belongs to the category of unsupervised learning and plays an important role in the dynamic systems and big data. The clustering problem of sampled time-series data is undoubtedly much more challenging than that of repeatable sampling ...
Shaolin Hu
doaj   +1 more source

Using Permutations for Hierarchical Clustering of Time Series

Entropy, 2019
Two distances based on permutations are considered to measure the similarity of two time series according to their strength of dependency. The distance measures are used together with different linkages to get hierarchical clustering methods of time ...
Jose S. Cánovas, Antonio Guillamón, María Carmen Ruiz-Abellón   +2 more
doaj   +1 more source

Time Series Clustering with Topological and Geometric Mixed Distance

Mathematics, 2021
Time series clustering is an essential ingredient of unsupervised learning techniques. It provides an understanding of the intrinsic properties of data upon exploiting similarity measures.
Yunsheng Zhang, Qingzhang Shi, Jiawei Zhu, Jian Peng, Haifeng Li   +4 more
doaj   +1 more source

Clustering of multivariate time-series data [PDF]

Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 2002
A new methodology for clustering multivariate time-series data is proposed. The methodology is based on calculation of the degree of similarity between multivariate time-series datasets using two similarity factors. One similarity factor is based on principal component analysis and the angles between the principal component subspaces while the other is
Ashish Singhal, Dale E. Seborg
openaire   +1 more source

Data-Adaptive Dynamic Time Warping-Based Multivariate Time Series Fuzzy Clustering

IEEE Access
Multivariate time series (MTS) clustering has become a critical research area. Current methods typically rely on space projection or representation learning for clustering but tend to overlook the significance and contribution of MTS dimensions, leading ...
Qinglin Cai, Leiying Chen, Jian Shao, Ling Chen   +3 more
doaj   +1 more source