Time series clustering based on the characterisation of segment typologies

Áreas de investigación:

• Methodology - Time series

Año:

2021

Tipo de publicación:

Artículo

Palabras clave:

Time series clustering, data mining, segmentation, feature extraction

Autores:

• Guijo-Rubio, David
• Durán-Rosal, Antonio Manuel
• Gutiérrez, Pedro Antonio
• Troncoso, Alicia
• Hervás-Martínez, César

Journal:

IEEE Transactions on Cybernetics

Volumen:

51

Número:

11

Páginas:

5409-5422

Mes:

November

ISSN:

2168-2267

BibTex:

@article{ClusteringGuijo19, author = "David Guijo-Rubio and Antonio Manuel Dur{\'a}n-Rosal and Pedro Antonio Guti{\'e}rrez and Alicia Troncoso and C{\'e}sar Herv{\'a}s-Mart{\'i}nez", awards = "JCR(2021): 19.118 Position: 3/144 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE", comments = "JCR(2021): 19.118 Position: 3/144 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE", doi = "10.1109/TCYB.2019.2962584", issn = "2168-2267", journal = "IEEE Transactions on Cybernetics", keywords = "Time series clustering, data mining, segmentation, feature extraction", month = "November", note = "JCR(2021): 19.118 Position: 3/144 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE", number = "11", pages = "5409--5422", title = "{T}ime series clustering based on the characterisation of segment typologies", url = "doi.org/10.1109/TCYB.2019.2962584", volume = "51", year = "2021", }

Nota:

JCR(2021): 19.118 Position: 3/144 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Comentarios:

JCR(2021): 19.118 Position: 3/144 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE