RT info:eu-repo/semantics/article
T1 Clustering Techniques Selection for a Hybrid Regression Model: A Case Study Based on a Solar Thermal System
A1 García Ordás, María Teresa
A1 Alaiz Moretón, Héctor
A1 Casteleiro Roca, José Luis
A1 Jove, Esteban
A1 Benítez Andrades, José Alberto
A1 García Rodríguez, Isaías
A1 Quintián, Héctor
A1 Calvo‐Rolle, José Luis
A2 Ingenieria de Sistemas y Automatica
K1 Informática
K1 Ingenierías
K1 Agglomerative Clustering
K1 clustering
K1 Gaussian Mixture
K1 hybrid model
K1 K-Means
K1 Spectral Clustering
K1 3306 Ingeniería y Tecnología Eléctricas
K1 33 Ciencias Tecnológicas
AB [EN] This work addresses the performance comparison between four clustering techniques with the objective of achieving strong hybrid models in supervised learning tasks. A real dataset from a bio-climatic house named Sotavento placed on experimental wind farm and located in Xermade (Lugo) in Galicia (Spain) has been collected. Authors have chosen the thermal solar generation system in order to study how works applying several cluster methods followed by a regression technique to predict the output temperature of the system. With the objective of defining the quality of each clustering method two possible solutions have been implemented. The first one is based on three unsupervised learning metrics (Silhouette, Calinski-Harabasz and Davies-Bouldin) while the second one, employs the most common error measurements for a regression algorithm such as Multi Layer Perceptron.
PB Taylor and Francis
SN 0196-9722
LK https://hdl.handle.net/10612/18242
UL https://hdl.handle.net/10612/18242
NO García-Ordás, M. T., Alaiz-Moretón, H., Casteleiro-Roca, J.-L., Jove, E., Benítez-Andrades, J. A., García-Rodríguez, I., Quintián, H., & Calvo-Rolle, J. L. (2023). Clustering Techniques Selection for a Hybrid Regression Model: A Case Study Based on a Solar Thermal System. Cybernetics and Systems, 54(3), 286-305. https://doi.org/10.1080/01969722.2022.2030006
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 18-may-2024