| Nome |
# |
|
Time Series Clustering by a Robust Autoregressive Metric with Application to Air Pollution, file e3835315-0233-15e8-e053-a505fe0a3de9
|
415
|
|
Time series clustering and classification, file e3835323-f028-15e8-e053-a505fe0a3de9
|
379
|
|
Fuzzy clustering of fuzzy data based on robust loss functions and ordered weighted averaging, file e3835323-bba9-15e8-e053-a505fe0a3de9
|
350
|
|
Fuzzy clustering with spatial–temporal information, file e3835323-a8af-15e8-e053-a505fe0a3de9
|
279
|
|
22 Fuzzy Clustering in Travel and Tourism Analytics, file e3835323-fbfe-15e8-e053-a505fe0a3de9
|
278
|
|
Robust fuzzy clustering based on quantile autocovariances, file e3835323-a8b1-15e8-e053-a505fe0a3de9
|
272
|
|
Atheoretical Regression Trees for classifying risky financial institutions, file e3835323-d295-15e8-e053-a505fe0a3de9
|
264
|
|
Exponential distance-based fuzzy clustering for interval-valued data, file e3835314-f61a-15e8-e053-a505fe0a3de9
|
262
|
|
A robust hierarchical clustering for georeferenced data, file e3835326-9d5b-15e8-e053-a505fe0a3de9
|
261
|
|
Quantile autocovariances: a powerful tool for hard and soft partitional clustering of time series, file e3835317-8904-15e8-e053-a505fe0a3de9
|
244
|
|
Fuzzy C-ordered medoids clustering of interval-valued data, file e3835315-3fbd-15e8-e053-a505fe0a3de9
|
240
|
|
Visualizing regional clusters of Sardinia's EU supported agriculture: A Spatial Fuzzy Partitioning Around Medoids, file e3835323-bd4c-15e8-e053-a505fe0a3de9
|
216
|
|
Cross Sectional and Longitudinal Fuzzy Clustering of the NUTS and Positioning of the Italian Regions with Respect to the Regional Competitiveness Index (RCI) Indicators with Contiguity Constraints, file e3835323-bba7-15e8-e053-a505fe0a3de9
|
179
|
|
Regime change analysis of interval-valued time series with an application to PM10, file e3835315-0982-15e8-e053-a505fe0a3de9
|
175
|
|
Bagged fuzzy clustering for fuzzy data: An application to a tourism market, file e3835315-0984-15e8-e053-a505fe0a3de9
|
174
|
|
Unsupervised Learning, file e3835323-bd4e-15e8-e053-a505fe0a3de9
|
139
|
|
Fuzzy clustering, file e3835323-fbfc-15e8-e053-a505fe0a3de9
|
129
|
|
Fuzzy segmentation of postmodern tourists, file e3835314-f47b-15e8-e053-a505fe0a3de9
|
107
|
|
Fuzzy clustering of mixed data, file e3835323-d29f-15e8-e053-a505fe0a3de9
|
102
|
|
A D-vine copula-based quantile regression model with spatial dependence for COVID-19 infection rate in Italy, file e383532e-4f46-15e8-e053-a505fe0a3de9
|
82
|
|
Time-series clustering, file e3835323-ef82-15e8-e053-a505fe0a3de9
|
79
|
|
Trimmed fuzzy clustering of financial time series based on dynamic time warping, file e3835323-d29a-15e8-e053-a505fe0a3de9
|
70
|
|
INGARCH-based fuzzy clustering of count time series with a football application, file 8e379e12-9221-4dc0-9a43-d014c267121a
|
69
|
|
null, file e383532d-36e7-15e8-e053-a505fe0a3de9
|
65
|
|
Modeling Local BES Indicators by Copula-Based Bayesian Networks, file e383532d-28fd-15e8-e053-a505fe0a3de9
|
45
|
|
Spatial-temporal clustering based on B-splines: robust models with applications to COVID-19 pandemic, file e383532c-bd9b-15e8-e053-a505fe0a3de9
|
43
|
|
Smoothed self-organizing map for robust clustering, file e3835323-d298-15e8-e053-a505fe0a3de9
|
40
|
|
Fuzzy clustering of spatial interval-valued data, file 28983a64-4ceb-4557-9f98-6bfaaf82e8df
|
30
|
|
null, file e383532e-15f5-15e8-e053-a505fe0a3de9
|
28
|
|
Exploratory multivariate analysis for empirical information affected by uncertainty and modeled in a fuzzy manner: a review, file e3835317-8903-15e8-e053-a505fe0a3de9
|
20
|
|
A centocinquant’anni da Roma capitale. Costruire il futuro della Città eterna, file e3835328-a6a4-15e8-e053-a505fe0a3de9
|
17
|
|
GARCH-based Robust Fuzzy Clustering of Time Series, file e3835315-3fbb-15e8-e053-a505fe0a3de9
|
16
|
|
Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques, file a48ce15d-f892-427e-ad03-858773fb8f71
|
15
|
|
A Tourist Segmentation Based on Motivation, Satisfaction and Prior Knowledge with a Socio-Economic Profiling: A Clustering Approach with Mixed Information, file e383532e-f443-15e8-e053-a505fe0a3de9
|
13
|
|
The gender gap in lifespan disparity as a social indicator of international countries: A fuzzy clustering approach, file 5e60c62c-cd6f-41c3-b974-5a26c9d2a128
|
11
|
|
A Bayesian network to analyse basketball players' performances: a multivariate copula-based approach, file 9b24b5ac-6c43-44fe-8046-63dedf3b45aa
|
8
|
|
Robust fuzzy clustering of multivariate time trajectories, file e383531b-5ee1-15e8-e053-a505fe0a3de9
|
6
|
|
Clustering of the italian regions based on their equitable and sustainable well-being indicators: a three-way approach, file e383532b-ea16-15e8-e053-a505fe0a3de9
|
5
|
|
To Share or not to Share? Determinants of Sharing Mobility in Italy, file e383532b-ee63-15e8-e053-a505fe0a3de9
|
5
|
|
A Regression Tree-Based Analysis of the European Regional Competitiveness, file e383532d-8981-15e8-e053-a505fe0a3de9
|
5
|
|
A Three-Way Approach for Defining Competitiveness Indexes of the European Regions (NUTS-2), file e383532d-a3e2-15e8-e053-a505fe0a3de9
|
5
|
|
Wavelet-based fuzzy clustering of interval time series, file 989cc1a1-ea0e-4aaa-ad2f-eae255ec8f89
|
3
|
|
Consumer behaviour and online advertising: A fuzzy approach to the market segmentation, file e3835318-cf5b-15e8-e053-a505fe0a3de9
|
3
|
|
Autoregressive metric-based trimmed fuzzy clustering with an application to PM10 time series, file e383531e-21c7-15e8-e053-a505fe0a3de9
|
3
|
|
The local press as an external public governance power, file 3192d3d3-28dc-4a66-8805-a5baf8e18d2f
|
2
|
|
FITTING OF FUZZY LINEAR REGRESSION MODELS WITH MULTIVARIATE RESPONSE, file e3835311-8e92-15e8-e053-a505fe0a3de9
|
2
|
|
Least squares estimation of a linear regression model with LR fuzzy response, file e3835311-9dbf-15e8-e053-a505fe0a3de9
|
2
|
|
A weighted fuzzy c-means clustering model for fuzzy data, file e3835311-d000-15e8-e053-a505fe0a3de9
|
2
|
|
Trimmed fuzzy clustering for interval-valued data, file e383531b-9b1f-15e8-e053-a505fe0a3de9
|
2
|
|
Analysing cluster evolution using repeated cross-sectional ordinal data, file e383531b-b374-15e8-e053-a505fe0a3de9
|
2
|
|
Complex networks and deep learning for copper flow across countries, file 56699abf-08b9-4d2d-8f48-10b96efa5afd
|
1
|
|
Quantile-based fuzzy clustering of multivariate time series in the frequency domain, file 57b0d50d-f715-41df-9cc3-fbc142edac36
|
1
|
|
Entropy-based fuzzy clustering of interval-valued time series, file 809d8dfb-e489-4d5f-83e3-631769025a96
|
1
|
|
Spatial Weighted Robust Clustering of Multivariate Time Series Based on Quantile Dependence With an Application to Mobility During COVID-19 Pandemic, file 93acf474-9777-4f92-b674-6b1826f261a7
|
1
|
|
A least squares approach to principal component analysis for interval valued data, file e3835311-8482-15e8-e053-a505fe0a3de9
|
1
|
|
A possibilistic approach to latent component analysis for symmetric fuzzy data, file e3835311-9458-15e8-e053-a505fe0a3de9
|
1
|
|
FUZZY K-MEDOIDS CLUSTERING MODELS FOR FUZZY MULTIVARIATE TIME TRAJECTORIES, file e3835311-9cdb-15e8-e053-a505fe0a3de9
|
1
|
|
Informational paradigm and entropy-based dynamic clustering in a complete fuzzy framework, file e3835311-9f82-15e8-e053-a505fe0a3de9
|
1
|
|
Fuzzy clustering for space-time series using spatial autocorrelation information, file e3835311-9f83-15e8-e053-a505fe0a3de9
|
1
|
|
A robust fuzzy k-means clustering model for interval valued data, file e3835311-e49e-15e8-e053-a505fe0a3de9
|
1
|
|
Component models for fuzzy data, file e3835312-12aa-15e8-e053-a505fe0a3de9
|
1
|
|
A Fuzzy Clustering Model for Multivariate Spatial Time Series, file e3835312-185e-15e8-e053-a505fe0a3de9
|
1
|
|
Fuzzy and possibilistic clustering for fuzzy data, file e3835313-5e09-15e8-e053-a505fe0a3de9
|
1
|
|
Fuzzy c-Medoids Clustering Models for Time-Varying Data, file e3835315-ed0b-15e8-e053-a505fe0a3de9
|
1
|
|
An asymptotic test for symmetry of random variables based on fuzzy tools, file e3835316-28c3-15e8-e053-a505fe0a3de9
|
1
|
|
Fuzzy clustering of time series using extremes, file e3835317-4ece-15e8-e053-a505fe0a3de9
|
1
|
|
Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review, file e3835317-8077-15e8-e053-a505fe0a3de9
|
1
|
|
Cepstral-based clustering of financial time series, file e383532a-bcd6-15e8-e053-a505fe0a3de9
|
1
|
|
null, file e383532d-1111-15e8-e053-a505fe0a3de9
|
1
|
| Totale |
5.182 |