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1 |
Scalable Labeling of Big Time-Series Data Based on Ensembles of Clustering Models and Weak Supervision
Berlin : Prior Art Publishing GmbH, 2024, Date:2024-12-12; File(MD5):93B67F0C732C83FD05FA7B69AB573181
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2 |
Trend triplet based data clustering for eliminating nonlinear trend components of wind time series to improve the performance of statistical forecasting models
Enthalten in Multimedia tools and applications 21.4.2022: 1-27
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3 |
Coastal change patterns from time series clustering of permanent laser scan data
Enthalten in Earth surface dynamics Bd. 9, 2021, Nr. 1: 89-103
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4 |
Coastal Change Patterns from Time Series Clustering of Permanent Laser Scan Data
Enthalten in Earth surface dynamics discussions 2020: 1-29
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5 |
A fragmented-periodogram approach for clustering big data time series
Enthalten in Advances in data analysis and classification 14.6.2019: 1-30
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6 |
Time series clustering based on sparse subspace clustering algorithm and its application to daily box-office data analysis
Enthalten in Neural computing & applications 21.9.2018: 1-10
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7 |
Time series distance measures
Spiegel, Stephan. - Berlin : Technische Universität Berlin, 2015
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8 |
Clustering Time Series with Clipped Data
Enthalten in Machine learning Bd. 58, Nr. 2-3, date:2.2005: 151-178
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9 |
Model-Based clustering for cross-sectional time series data
Enthalten in Journal of agricultural, biological, and environmental statistics Bd. 7, Nr. 1, date:3.2002: 107-127
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10 |
A clustering algorithm for detecting differential deviations in the multivariate time-series IoT data based on sensor relationship
Enthalten in Knowledge and information systems Bd. 67, 17.12.2024, Nr. 3, date:3.2025: 2641-2690
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