Alpha V. Pernía-Espinoza

发表

Towards Improving the Applicability of Non-parametric Multiple Comparisons to Select the Best Soft Computing Models in Rubber Extrusion Industry

Andrés Sanz-García, Ruben Urraca-Valle, Enrique Sodupe-Ortega, 2013, SOCO-CISIS-ICEUTE.

Single and Blended Models for Day-Ahead Photovoltaic Power Forecasting

Rubén Urraca, Alvaro Aldama, Francisco Javier Martínez de Pisón, 2017, HAIS.

TAO-robust backpropagation learning algorithm

Ana González-Marcos, Joaquín B. Ordieres Meré, Francisco J. Martínez de Pisón Ascacibar, 2005, Neural Networks.

A Straightforward Implementation of a GPU-accelerated ELM in R with NVIDIA Graphic Cards

M. Alia-Martinez, Rubén Urraca, Alpha V. Pernía-Espinoza, 2015, HAIS.

GAparsimony: An R Package for Searching Parsimonious Models by Combining Hyperparameter Optimization and Feature Selection

Francisco Javier Martínez de Pisón, Alpha V. Pernía-Espinoza, Javier Ferreiro-Cabello, 2018, HAIS.

Genetic Algorithms Combined with the Finite Elements Method as an Efficient Methodology for the Design of Tapered Roller Bearings

Ana González-Marcos, Andrés Sanz-García, Alpha V. Pernía-Espinoza, 2011, SOCO.

Improving Steel Industrial Processes Using Genetic Algorithms and Finite Element Method

Andrés Sanz-García, Francisco J. Martínez de Pisón Ascacibar, Alpha V. Pernía-Espinoza, 2011, SOCO.

Combining genetic algorithms and the finite element method to improve steel industrial processes

Andrés Sanz-García, Francisco J. Martínez de Pisón Ascacibar, Alpha V. Pernía-Espinoza, 2012, J. Appl. Log..

Hotel Reservation Forecasting Using Flexible Soft Computing Techniques: A Case of Study in a Spanish Hotel

Andrés Sanz-García, Francisco J. Martínez de Pisón Ascacibar, Alpha V. Pernía-Espinoza, 2016, Int. J. Inf. Technol. Decis. Mak..

Stacking ensemble with parsimonious base models to improve generalization capability in the characterization of steel bolted components

Rubén Urraca, Javier Antoñanzas-Torres, Francisco J. Martínez de Pisón Ascacibar, 2018, Appl. Soft Comput..

Searching Parsimonious Solutions with GA-PARSIMONY and XGBoost in High-Dimensional Databases

Francisco J. Martínez de Pisón Ascacibar, Alpha V. Pernía-Espinoza, Javier Ferreiro-Cabello, 2016, SOCO-CISIS-ICEUTE.

Technical projects with social commitment for teaching-learning intervention in STEM students

Andrés Sanz-García, Alpha V. Pernía-Espinoza, Francisco Javier Martínez de Pisón Ascacíbar, 2020, 2020 IEEE Global Engineering Education Conference (EDUCON).

GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace

Andrés Sanz-García, Francisco J. Martínez de Pisón Ascacibar, Alpha V. Pernía-Espinoza, 2015, Appl. Soft Comput..

A neural network-based approach for optimising rubber extrusion lines

Ana González-Marcos, Fernando Alba-Elías, Alpha V. Pernía-Espinoza, 2007, Int. J. Comput. Integr. Manuf..

Improving hotel room demand forecasting with a hybrid GA-SVR methodology based on skewed data transformation, feature selection and parsimony tuning

Rubén Urraca, Andrés Sanz-García, Francisco J. Martínez de Pisón Ascacibar, 2017, Log. J. IGPL.

Active learning methodologies in STEM degrees jeopardized by COVID19

Andrés Sanz-García, Francisco J. Martínez de Pisón Ascacibar, Fermín Navaridas-Nalda, 2021, 2021 IEEE Global Engineering Education Conference (EDUCON).