Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Morales Hernández, Alejandro"'
The performance of any Machine Learning (ML) algorithm is impacted by the choice of its hyperparameters. As training and evaluating a ML algorithm is usually expensive, the hyperparameter optimization (HPO) method needs to be computationally efficien
Externí odkaz:
http://arxiv.org/abs/2209.04340
Autor:
Morales-Hernández, Alejandro, Gonzalez, Sebastian Rojas, Van Nieuwenhuyse, Inneke, Couckuyt, Ivo, Jordens, Jeroen, Witters, Maarten, Van Doninck, Bart
Adhesive joints are increasingly used in industry for a wide variety of applications because of their favorable characteristics such as high strength-to-weight ratio, design flexibility, limited stress concentrations, planar force transfer, good dama
Externí odkaz:
http://arxiv.org/abs/2112.08760
Autor:
Morales-Hernández, Alejandro, Van Nieuwenhuyse, Inneke, Gonzalez, Sebastian Rojas, Jordens, Jeroen, Witters, Maarten, Van Doninck, Bart
Automotive companies are increasingly looking for ways to make their products lighter, using novel materials and novel bonding processes to join these materials together. Finding the optimal process parameters for such adhesive bonding process is cha
Externí odkaz:
http://arxiv.org/abs/2112.06769
Autor:
Jastrzebska, Agnieszka, Morales-Hernández, Alejandro, Nápoles, Gonzalo, Salgueiro, Yamisleydi, Vanhoof, Koen
Time series processing is an essential aspect of wind turbine health monitoring. Despite the progress in this field, there is still room for new methods to improve modeling quality. In this paper, we propose two new approaches for the analysis of win
Externí odkaz:
http://arxiv.org/abs/2112.04933
Hyperparameter optimization (HPO) is a necessary step to ensure the best possible performance of Machine Learning (ML) algorithms. Several methods have been developed to perform HPO; most of these are focused on optimizing one performance measure (us
Externí odkaz:
http://arxiv.org/abs/2111.13755
Autor:
Morales-Hernández, Alejandro, Nápoles, Gonzalo, Jastrzebska, Agnieszka, Salgueiro, Yamisleydi, Vanhoof, Koen
Forecasting windmill time series is often the basis of other processes such as anomaly detection, health monitoring, or maintenance scheduling. The amount of data generated on windmill farms makes online learning the most viable strategy to follow. S
Externí odkaz:
http://arxiv.org/abs/2107.00425
Autor:
Morales-Hernández, Alejandro a, Nápoles, Gonzalo b, ⁎, Jastrzebska, Agnieszka c, Salgueiro, Yamisleydi d, Vanhoof, Koen a
Publikováno v:
In Expert Systems With Applications 1 November 2022 205
Autor:
Jastrzebska, Agnieszka a, ∗, Morales Hernández, Alejandro b, Nápoles, Gonzalo c, Salgueiro, Yamisleydi d, Vanhoof, Koen b
Publikováno v:
In Renewable Energy May 2022 190:730-740
Autor:
Morales-Hernández, Alejandro, Rojas Gonzalez, Sebastian, Van Nieuwenhuyse, Inneke, Couckuyt, Ivo, Jordens, Jeroen, Witters, Maarten, Van Doninck, Bart
Publikováno v:
Engineering with Computers; Aug2024, Vol. 40 Issue 4, p2497-2511, 15p
Autor:
Cabrera-Hernández, Leidys1 leidysc@uclv.edu.cu, Morales Hernández, Alejandro1, Meneses Gómez, Maricel2, Meneses Marcel, Alfredo2, Casas Cardoso, Gladys M.1, García Lorenzo, María M.1 mmgarcia@uclv.edu.cu
Publikováno v:
Investigación Operacional. 2021, Vol. 42 Issue 4, p495-509. 15p.