FUZZY C-MEANS CLUSTERING MODELS FOR MULTIVARIATE TIME-VARYING DATA: DIFFERENT APPROACHES

DOI10.1142/S0218488504002849zbMath1046.62061OpenAlexW2151256021MaRDI QIDQ4819224

Pierpaolo D'Urso

Publication date: 24 September 2004

Published in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218488504002849

zbMATH Keywords

trendvelocityaccelerationpanel datapositiontime-lagexploratory approachcluster-validitycross sectionalevolutive clusteringinternal and external time weighting systemslongitudinal fuzzy classificationsingle and double step proceduresthree-way data time arraystime trajectory

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (20)

Robust fuzzy clustering of multivariate time trajectories ⋮ Robust multivariate and functional archetypal analysis with application to financial time series analysis ⋮ Dense traffic flow patterns mining in bi-directional road networks using density based trajectory clustering ⋮ OWA-based robust fuzzy clustering of time series with typicality degrees ⋮ Wavelets-based clustering of multivariate time series ⋮ Fuzzy clustering of time series using extremes ⋮ A new distance with derivative information for functional \(k\)-means clustering algorithm ⋮ KmL: k-means for longitudinal data ⋮ Noise fuzzy clustering of time series by autoregressive metric ⋮ Model-based fuzzy time series clustering of conditional higher moments ⋮ Robust fuzzy clustering of time series based on B-splines ⋮ Trimmed fuzzy clustering of financial time series based on dynamic time warping ⋮ Fuzzy unsupervised classification of multivariate time trajectories with the Shannon entropy regularization ⋮ Fuzzy clustering of time series in the frequency domain ⋮ GARCH-based robust clustering of time series ⋮ Crisp and fuzzy k-means clustering algorithms for multivariate functional data ⋮ Robust fuzzy clustering based on quantile autocovariances ⋮ Time-varying clustering of multivariate longitudinal observations ⋮ A fuzzy clustering model for multivariate spatial time series ⋮ Wavelet-based fuzzy clustering of time series

Uses Software

• J-MEANS

Cites Work

• Three-way fuzzy clustering models for LR fuzzy time trajectories
• GENNCLUS: New models for general nonhierarchical clustering analysis
• Pattern classification problems and fuzzy sets
• Numerical taxonomy with fuzzy sets
• Optimization methods for fuzzy clustering
• A new time series classification approach
• Fuzzy clustering using scatter matrices
• Fuzzy clustering models and applications
• Clusters of time series
• Fuzzy rule based classification with FeatureSelector and modified threshold accepting
• Fuzzy \(K\)-means clustering models for triangular fuzzy time trajectories
• Cluster analysis of the realizations of autoregression time series
• Fuzzy J-means: a new heuristic for fuzzy clustering
• Abstraction and pattern classification
• A metric for ARMA processes
• A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS
• A two‐step procedure for clustering time varying data
• c-means clustering with the l/sub l/ and l/sub infinity / norms
• A new cluster validity index for the fuzzy c-mean
• A significance test for classifying arma models
• Collaborative fuzzy clustering
• A new approach to clustering
• Bayesian clustering by dynamics
• A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters

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