Search

Your search keyword '"García-Gonzalo, Esperanza"' showing total 144 results
Start Over Author "García-Gonzalo, Esperanza"
144 results on '"García-Gonzalo, Esperanza"'

7. Time Series Forecasting of Gold Prices with the Help of Its Decomposition and Multivariate Adaptive Regression Splines

Author

Lasheras, Fernando Sánchez, Nieto, Paulino José García, García-Gonzalo, Esperanza, Valverde, Gregorio Fidalgo, Krzemień, Alicja, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sanjurjo González, Hugo, editor, Pastor López, Iker, editor, García Bringas, Pablo, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2022
Full Text
View/download PDF

8. Time Series Analysis for the COMEX Gold Spot Price Forecasting by Using NARX DE/SVR and DE/GPR Techniques

Author

García-Gonzalo, Esperanza, Nieto, Paulino José García, Valverde, Gregorio Fidalgo, Fernández, Pedro Riesgo, Lasheras, Fernando Sánchez, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sanjurjo González, Hugo, editor, Pastor López, Iker, editor, García Bringas, Pablo, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2022
Full Text
View/download PDF

10. Time Series Analysis for the COMEX Copper Spot Price by Using Support Vector Regression

Author

García-Gonzalo, Esperanza, García Nieto, Paulino José, Gracia Rodríguez, Javier, Sánchez Lasheras, Fernando, Fidalgo Valverde, Gregorio, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herrero, Álvaro, editor, Cambra, Carlos, editor, Urda, Daniel, editor, Sedano, Javier, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2021
Full Text
View/download PDF

11. A Multivariate Approach to Time Series Forecasting of Copper Prices with the Help of Multiple Imputation by Chained Equations and Multivariate Adaptive Regression Splines

Author

Sánchez Lasheras, Fernando, Gracia Rodríguez, Javier, García Nieto, Paulino José, García-Gonzalo, Esperanza, Fidalgo Valverde, Gregorio, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herrero, Álvaro, editor, Cambra, Carlos, editor, Urda, Daniel, editor, Sedano, Javier, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2021
Full Text
View/download PDF

14. Missing Data Imputation for Continuous Variables Based on Multivariate Adaptive Regression Splines

Author

Sánchez Lasheras, Fernando, García Nieto, Paulino José, García-Gonzalo, Esperanza, Argüeso Gómez, Francisco, Rodríguez Iglesias, Francisco Javier, Suárez Sánchez, Ana, Santos Rodríguez, Jesús Daniel, Sánchez, María Luisa, González-Nuevo, Joaquín, Bonavera, Laura, Toffolatti, Luigi, Fernández Menéndez, Susana del Carmen, de Cos Juez, Francisco Javier, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, de la Cal, Enrique Antonio, editor, Villar Flecha, José Ramón, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2020
Full Text
View/download PDF

30. A support vector regression model for time series forecasting of the COMEX copper spot price.

Author

García-Gonzalo, Esperanza, Nieto, Paulino José García, Rodríguez, Javier Gracia, Lasheras, Fernando Sánchez, and Valverde, Gregorio Fidalgo

Subjects
SPOT prices, COPPER prices, REGRESSION analysis, FORECASTING, COMMODITY exchanges
Abstract

The price of copper is unstable but it is considered an important indicator of the global economy. Changes in the price of copper point to higher global growth or an impending recession. In this work, the forecasting of the spot prices of copper from the New York Commodity Exchange is studied using a machine learning method, support vector regression coupled with different model schemas (recursive, direct and hybrid multi-step). Using these techniques, three different time series analyses are built and its performance are compared. The numerical results show that the hybrid direct-recursive obtains the best results. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

31. Aligned PSO for Optimization of Image Processing Methods Applied to the Face Recognition Problem

Author

Fernández-Martínez, Juan Luis, Cernea, Ana, García-Gonzalo, Esperanza, Velasco, Julian, Panigrahi, Bijaya Ketan, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Panigrahi, Bijaya Ketan, editor, Suganthan, Ponnuthurai Nagaratnam, editor, Das, Swagatam, editor, and Dash, Shubhransu Sekhar, editor

Published
2013
Full Text
View/download PDF

33. Particle Swarm Optimization: A Powerful Family of Stochastic Optimizers. Analysis, Design and Application to Inverse Modelling

Author

Fernández-Martínez, Juan Luis, García-Gonzalo, Esperanza, Saraswathi, Saras, Jernigan, Robert, Kloczkowski, Andrzej, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Tan, Ying, editor, Shi, Yuhui, editor, Chai, Yi, editor, and Wang, Guoyin, editor

Published
2011
Full Text
View/download PDF

34. Particle Swarm Optimization and Inverse Problems

Author

García-Gonzalo, Esperanza, Fernández-Martínez, Juan Luis, Kacprzyk, Janusz, editor, Borgelt, Christian, editor, González-Rodríguez, Gil, editor, Trutschnig, Wolfgang, editor, Lubiano, María Asunción, editor, Gil, María Ángeles, editor, Grzegorzewski, Przemysław, editor, and Hryniewicz, Olgierd, editor

Published
2010
Full Text
View/download PDF

35. PSO Advances and Application to Inverse Problems

Author

Fernández-Martínez, Juan Luis, García-Gonzalo, Esperanza, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Panigrahi, Bijaya Ketan, editor, Das, Swagatam, editor, Suganthan, Ponnuthurai Nagaratnam, editor, and Dash, Subhransu Sekhar, editor

Published
2010
Full Text
View/download PDF

36. Particle Swarm Optimization in High Dimensional Spaces

Author

Fernández-Martínez, Juan L., Mukerji, Tapan, García-Gonzalo, Esperanza, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Dorigo, Marco, editor, Birattari, Mauro, editor, Di Caro, Gianni A., editor, Doursat, René, editor, Engelbrecht, Andries P., editor, Floreano, Dario, editor, Gambardella, Luca Maria, editor, Groß, Roderich, editor, Şahin, Erol, editor, Sayama, Hiroki, editor, and Stützle, Thomas, editor

Published
2010
Full Text
View/download PDF

39. Chrome Layer Thickness Modelling in a Hard Chromium Plating Process Using a Hybrid PSO/ RBF–SVM–Based Model

Author

García Nieto, P. J., García Gonzalo, Esperanza, Sánchez Lasheras, Fernando, Sánchez, Antonio Bernardo, García Nieto, P. J., García Gonzalo, Esperanza, Sánchez Lasheras, Fernando, and Sánchez, Antonio Bernardo

Abstract

The purpose of chromium plating is the creation of a hard and wear-resistant layer of chromium over a metallic surface. The principal feature of chromium plating is its endurance in the face of the wear and corrosion. This industrial process has a vast range of applications in many different areas. In the performance of this process, some difficulties can be found. Some of the most common are melt deposition, milky white chromium deposition, rough or sandy chromium deposition and lack of toughness of the layer or wear and lack of thickness of the layer deposited. This study builds a novel nonparametric method relied on the statistical machine learning that employs a hybrid support vector machines (SVMs) model for the hard chromium layer thickness forecast. The SVM hyperparameters optimization was made with the help of the Particle Swarm Optimizer (PSO). The outcomes indicate that PSO/SVM–based model together with radial basis function (RBF) kernel has permitted to foretell the thickness of the chromium layer created in this industrial process satisfactorily. Thus, two kinds of outcomes have been obtained: firstly, this model permits to determine the ranking of relevance of the seven independent input variables investigated in this industrial process. Finally, the high achievement and lack of complexity of the model indicate that the PSO/SVM method is very interesting compared to other conventional foretelling techniques, since a coefficient of determination of 0.9952 is acquired.

Published
2020

48. Chrome Layer Thickness Modelling in a Hard Chromium Plating Process Using a Hybrid PSO/RBF-SVM-Based Model.

Author

García Nieto, Paulino José, García-Gonzalo, Esperanza, Sánchez Lasheras, Fernando, and Bernardo Sánchez, Antonio

Subjects
RADIAL basis functions, SUPPORT vector machines, METALLIC surfaces, STATISTICAL learning, MANUFACTURING processes
Abstract

The purpose of chromium plating is the creation of a hard and wear-resistant layer of chromium over a metallic surface. The principal feature of chromium plating is its endurance in the face of the wear and corrosion. This industrial process has a vast range of applications in many different areas. In the performance of this process, some difficulties can be found. Some of the most common are melt deposition, milky white chromium deposition, rough or sandy chromium deposition and lack of toughness of the layer or wear and lack of thickness of the layer deposited. This study builds a novel nonparametric method relied on the statistical machine learning that employs a hybrid support vector machines (SVMs) model for the hard chromium layer thickness forecast. The SVM hyperparameters optimization was made with the help of the Particle Swarm Optimizer (PSO). The outcomes indicate that PSO/SVM-based model together with radial basis function (RBF) kernel has permitted to foretell the thickness of the chromium layer created in this industrial process satisfactorily. Thus, two kinds of outcomes have been obtained: firstly, this model permits to determine the ranking of relevance of the seven independent input variables investigated in this industrial process. Finally, the high achievement and lack of complexity of the model indicate that the PSO/SVM method is very interesting compared to other conventional foretelling techniques, since a coefficient of determination of 0.9952 is acquired. [ABSTRACT FROM AUTHOR]

Published
2020
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results