Results 71 to 80 of about 18,151,622 (163)

Time Series Overlapping Clustering Based on Link Community Detection

IEEE Access
Given the nature of time series and their vast applications, it is essential to find clustering algorithms that depict their real-life properties.
Yasamin Ghahremani, Babak Amiri
doaj   +1 more source

Feature-based clustering of global sea level anomaly time series

Scientific Reports
The efficiency of various sea level change prediction methods can be enhanced through clustering global sea levels, considering the high dimensionality, redundancy, and nonlinearity of sea level anomaly time series.
Qinting Sun, Jianhua Wan, Shanwei Liu
doaj   +1 more source

Multivariate Time Series Classification Algorithm Based on Heterogeneous Feature Fusion [PDF]

Jisuanji kexue
With the advance of big data and sensors,multivariable time series classification has been an important problem in data mining.Multivariate time series are characterized by high dimensionality,complex inter-dimensional relations,and variable data forms ...
QIAO Fan, WANG Peng, WANG Wei
doaj   +1 more source

Clustering financial time series [PDF]

, 2020
Time series clustering is heavily based on choosing a proper dissimilarity measure between a pair of time series. We present several dissimilarity measures and use two synthetic datasets to evaluate their performance. Hierarchical clustering and network
Potikyan, Nshan
core  

DYNAMIC TIME WARPING-BASED FUZZY C-MEANS WITH MULTIDIMENSIONAL SCALING FOR TIME SERIES CLUSTERING

Barekeng
Weather refers to atmospheric conditions such as temperature, humidity, air pressure, wind speed, and rainfall, all of which influence human activities.
Sri Hidayati, Regita Putri Permata, Fidi Wincoko Putro   +2 more
doaj   +1 more source

Multi-attribute fuzzy time series method based on fuzzy clustering

, 2015
[[abstract]]Traditional time series methods can predict the seasonal problem, but fail to forecast the problems with linguistic value. An alternative forecasting method such as fuzzy time series is utilized to deal with these kinds of problems.
王佳文;Wang, Jia-Wen;Cheng, Ching-Hsue;Cheng, Guang-Wei
core  

Clustering Time Series of Different Length Using Self-Organising Maps

The current work is devoted to the problem of time series analysis. One of the relevant tasks connected with time series is splitting the set of objects into individual groups – clusters for further forecasting the behaviour of time series.
Paršutins, Sergejs
core  

Is it Social Influence on Beliefs Under Ambiguity? A Possible Explanation for Volatility Clustering [PDF]

Influencing and being influenced by others is the very essence of human behaviour. We put forward an exploratory asset-pricing model allowing for social influence on investor judgments under ambiguity.
Hammad A. Siddiqi
core  

Temporal Multi-Features Representation Learning-Based Clustering for Time-Series Data

IEEE Access
Time-series clustering remains a challenge in data mining. Although novel deep-learning-based representation learning integrated with deep clustering methods have considerably enhanced the performance of time-series clustering, efficiently capturing the ...
Jaehoon Lee, Dohee Kim, Sunghyun Sim
doaj   +1 more source

BELMM: Bayesian model selection and random walk smoothing in time-series clustering. [PDF]

Bioinformatics, 2023
Sarala O, Pyhäjärvi T, Sillanpää MJ.
europepmc   +1 more source