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Your search keyword '"I. García"' showing total 9 results
Start Over Author "I. García" Publication Type Books
9 results on '"I. García"'

1. The Brain-Like Enteric Nervous System

Author

M.J. Caycho Salazar, Flower, primary, Herrera-Covarrubias, Deissy, additional, A. Coria-Ávila, Genaro, additional, I. García-Hernández, Luis, additional, Rebeca Toledo-Cárdenas, María, additional, Elena Hernández-Aguilar, María, additional, and Manzo, Jorge, additional

Published
2023
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2. Usefulness of the Hemogram in COVID-19

Author

Jimeno, Sara, primary, Peixoto, Alejandro, additional, Velázquez, Sara, additional, Sol Ventura, Paula, additional, I. García Adasme, Salvador, additional, and López-Escobar, Alejandro, additional

Published
2021
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6. Evolution of XPath Lists for Document Data Selection

Author

García-Sánchez, Pablo, primary, Guervós, Juan J. Merelo, additional, Castillo, Pedro Ángel, additional, González, Jesús, additional, Laredo, Juan L. Jiménez, additional, García, Antonio M. Mora, additional, and Arenas, Maria I. García, additional

Published
2010
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8. Evolution of XPath Lists for Document Data Selection.

Author

García-Sánchez, Pablo, Guervós, Juan J. Merelo, Castillo, Pedro Ángel, González, Jesús, Laredo, Juan L. Jiménez, García, Antonio M. Mora, and Arenas, Maria I. García

Abstract

XML has became a standard for structured data, and very often transformations from one specific format to another are needed. XSLT stylesheets are programs designed for this purpose, and they use XPath expressions to select sets of nodes within the document. In this paper a new version of an evolutionary algorithm that creates XSLT from examples is presented, improving on previously obtained results by testing a new individual representation with a new set of operators, based mainly on evolution of XPaths with a fixed XSLT program structure. The experiments show that this new representation, and a lower set of operators, yield better results in less generations that in our previous version. [ABSTRACT FROM AUTHOR]

Published
2011
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9. Statistical Analysis of Parameter Setting in Real-Coded Evolutionary Algorithms.

Author

Arenas, Maria I. García, Valdivieso, Pedro Ángel Castillo, García, Antonio M. Mora, Guervós, Juan J. Merelo, Laredo, Juan L. Jiménez, and García-Sánchez, Pablo

Abstract

When evolutionary algorithm (EA) applications are being developed it is very important to know which parameters have the greatest influence on the behavior and performance of the algorithm. This paper proposes using the ANOVA (ANalysis Of the VAriance) method to carry out an exhaustive analysis of an EA method and the different parameters it requires, such as those related to the number of generations, population size, operators application and selection type. When undertaking a detailed statistical analysis of the influence of each parameter, the designer should pay attention mostly to the parameter presenting values that are statistically most significant. Following this idea, the significance and relative importance of the parameters with respect to the obtained results, as well as suitable values for each of these, were obtained using ANOVA on four well known function optimization problems. [ABSTRACT FROM AUTHOR]

Published
2011
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