An evolutionary triclustering approach to discover electricity consumption patterns in France
Author:
Affiliation:
1. University of Seville, Seville, Spain
2. Pablo de Olavide University, Seville, Spain
3. Université Lumière Lyon 2, Lyon, France
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3605098.3636034
Reference31 articles.
1. J. L. Amaro-Mellado, L. Melgar-García, C. Rubio-Escudero, and D. Gutiérrez-Avilés. 2021. Generating a seismogenic source zone model for the Pyrenees: A GIS-assisted triclustering approach. Computers & Geosciences 150 (5 2021), 104736.
2. Triclustering of gene expression microarray data using coarse grained and dynamic deme based parallel genetic approach
3. TriRNSC: triclustering of gene expression microarray data using restricted neighbourhood search
4. TRIQ: a new method to evaluate triclusters
5. D. Gutiérrez-Avilés and C. Rubio-Escudero. 2014. LSL: A new measure to evaluate triclusters. In Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 30--37.
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