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DEFENSA DE TESIS DOCTORAL: INCREMENTAL ALGORITHM FOR DECISION RULE GENERATION IN DATA STREAM CONTEXTS

DEFENSA DE TESIS DOCTORAL
Título: INCREMENTAL ALGORITHM FOR DECISION RULE GENERATION IN DATA STREAM CONTEXTS
Autora: Nuria Mollá Campello
Directores: Dr.  Antonio Ferrándiz Colmeiro (TERALCO GROUP), Dr. Alejandro Rabasa Dolado y Dr. Joaquín Sánchez Soriano (Universidad Miguel Hernández de Elche)
Fecha: Lunes 30 de enero de 2023 a las 11:00h
Lugar: Thinking Lab CIO

Aparicio, J., Kapelko, M., Ortiz, L. (2023) "Enhancing the Measurement of Firm Inefficiency Accounting for Corporate Social Responsibility: A Dynamic Data Envelopment Analysis Fuzzy Approach", European Journal of Operational Research, 306 (2):986–997

Juan Aparicio, Lidia Ortiz(Operations Research Center, University Miguel Hernández of Elche) and Magdalena Kapelko (Wrocław University of Economics and Business)
Abstract: This paper contributes to research on the corporate social responsibility (CSR) field and the inefficiency measurement of firms by proposing a new method for evaluating inefficiency accounting for firms’ CSR activities. The new approach considers […]

Bugallo, M., Esteban, M.D., Marey-Pérez, M.F., Morales, D. (2023) “Wildfire prediction using zero-inflated negative binomial mixed models: Application to Spain”, Journal of Environmental Management, 328:116788

María Bugallo, María Dolores Esteban, Domingo Morales (Operations Research Center, University Miguel Hernández of Elche) and Manuel Francisco Marey-Pérez (Universidad de Santiago de Compostela, Escuela Politécnica Superior de Ingeniería, Spain)
Abstract: Wildfires have changed in recent decades. The catastrophic wildfires make it necessary to have accurate predictive models on a country scale to organize firefighting resources. […]

Labbé, M., Landete, M., Leal, M. (2023) “Dendrograms, minimum spanning trees and feature selection”, European Journal of Operational Research

Martine Labbé (Computer Science Department, Université Libre de Bruxelles, Belgium) Mercedes Landete and Marina Leal(Operations Research Center, University Miguel Hernández of Elche) and 
Abstract: Feature selection is a fundamental process to avoid overfitting and to reduce the size of databases without significant loss of information that applies to hierarchical clustering. Dendrograms are graphical representations of hierarchical clustering […]

Valero-Carreras, D., Alcaraz, J., Landete, M. (2023) "Comparing two SVM models through different metrics based on the confusion matrix", Computers and Operations Research, 152:106131

Daniel Valero Carreras, Javier Alcaraz and Mercedes Landete (Center of Operations Research, Miguel Hernández University of Elche) 
Abstract: Support Vector Machines (SVM) are an efficient alternative for supervised classification. In the soft margin SVM model, two different objectives are optimized and the set of alternative solutions represent a Pareto-front of points, each one of them representing a […]