Francisco Herrera - researchr alias

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2011

Soft Computing Techniques in Data MiningJesús Alcalá-Fdez, Francisco Herrera. mvl, 17(2-3):99-100, 2011. [doi]

A Fast and Scalable Multiobjective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression ProblemsRafael Alcalá, María José Gacto, Francisco Herrera. tfs, 19(4):666-681, 2011. [doi]

An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory fieldM. J. Cobo, Antonio Gabriel López-Herrera, Enrique Herrera-Viedma, Francisco Herrera. joi, 5(1):146-166, 2011. [doi]

Science mapping software tools: Review, analysis, and cooperative study among toolsM. J. Cobo, Antonio Gabriel López-Herrera, Enrique Herrera-Viedma, Francisco Herrera. jasis, 62(7):1382-1402, 2011. [doi]

A Preliminary Study on the Use of Fuzzy Rough Set Based Feature Selection for Improving Evolutionary Instance Selection AlgorithmsJoaquín Derrac, Chris Cornelis, Salvador García, Francisco Herrera. iwann 2011: 174-182 [doi]

Addressing the Classification with Imbalanced Data: Open Problems and New Challenges on Class DistributionAlberto Fernández, Salvador García, Francisco Herrera. HAIS 2011: 1-10 [doi]

A Double Axis Classification of Interpretability Measures for Linguistic Fuzzy Rule-Based SystemsMaría José Gacto, Rafael Alcalá, Francisco Herrera. wilf 2011: 99-106 [doi]

Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measuresMaría José Gacto, Rafael Alcalá, Francisco Herrera. isci, 181(20):4340-4360, 2011. [doi]

An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemesMikel Galar, Alberto Fernández, Edurne Barrenechea Tartas, Humberto Bustince Sola, Francisco Herrera. PR, 44(8):1761-1776, 2011. [doi]

Special issue on the trends in applied intelligence systemsNicolás García-Pedrajas, Francisco Herrera, Colin Fyfe. apin, 34(3):329-330, 2011. [doi]

Evolutionary selection of hyperrectangles in nested generalized exemplar learningSalvador García, Joaquín Derrac, Julián Luengo, Cristóbal J. Carmona, Francisco Herrera. asc, 11(3):3032-3045, 2011. [doi]

A genetic tuning to improve the performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of ignorance and lateral positionJosean Sanz, Alberto Fernández, Humberto Bustince Sola, Francisco Herrera. ijar, 52(6):751-766, 2011. [doi]

A methodology for Institution-Field ranking based on a bidimensional analysis: the ::::IFQ:::::::2:::::::A:::: indexDaniel Torres-Salinas, Jose G. Moreno-Torres, Emilio Delgado López-Cózar, Francisco Herrera. scientometrics, 88(3):771-786, 2011. [doi]

Enhancing IPADE Algorithm with a Different Individual CodificationIsaac Triguero, Salvador García, Francisco Herrera. HAIS 2011: 262-270 [doi]

Differential evolution for optimizing the positioning of prototypes in nearest neighbor classificationIsaac Triguero, Salvador García, Francisco Herrera. PR, 44(4):901-916, 2011. [doi]

2010

Analysis of the Effectiveness of the Genetic Algorithms based on Extraction of Association RulesJesús Alcalá-Fdez, Nicolò Flugy Papè, Andrea Bonarini, Francisco Herrera. FUIN, 98(1):1-14, 2010. [doi]

::::hg::::-index: a new index to characterize the scientific output of researchers based on the ::::h::::- and ::::g::::-indicesSergio Alonso, Francisco Javier Cabrerizo, Enrique Herrera-Viedma, Francisco Herrera. scientometrics, 82(2):391-400, 2010. [doi]

A web based consensus support system for group decision making problems and incomplete preferencesSergio Alonso, Enrique Herrera-Viedma, Francisco Chiclana, Francisco Herrera. isci, 180(23):4477-4495, 2010. [doi]

::::WoS:::: query partitioner: A tool to retrieve very large numbers of items from the ::::Web of Science:::: using different source-based partitioning approachesSergio Alonso, Francisco Javier Cabrerizo, Enrique Herrera-Viedma, Francisco Herrera. jasis, 61(8):1582-1597, 2010. [doi]

GP-COACH: Genetic Programming-based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problemsFrancisco José Berlanga, Antonio Jesús Rivera Rivas, María José del Jesús, Francisco Herrera. isci, 180(8):1183-1200, 2010. [doi]

q:::2:::-Index: Quantitative and qualitative evaluation based on the number and impact of papers in the Hirsch coreFrancisco Javier Cabrerizo, Sergio Alonso, Enrique Herrera-Viedma, Francisco Herrera. joi, 4(1):23-28, 2010. [doi]

NMEEF-SD: Non-dominated Multiobjective Evolutionary Algorithm for Extracting Fuzzy Rules in Subgroup DiscoveryCristóbal J. Carmona, Pedro González, María José del Jesús, Francisco Herrera. tfs, 18(5):958-970, 2010. [doi]

IFS-CoCo in the Landscape Contest: Description and ResultsJoaquín Derrac, Salvador García, Francisco Herrera. icpr 2010: 56-65 [doi]

A Survey on Evolutionary Instance Selection and GenerationJoaquín Derrac, Salvador García, Francisco Herrera. ijamc-igi, 1(1):60-92, 2010. [doi]

IFS-CoCo: Instance and feature selection based on cooperative coevolution with nearest neighbor ruleJoaquín Derrac, Salvador García, Francisco Herrera. PR, 43(6):2082-2105, 2010. [doi]

Stratified prototype selection based on a steady-state memetic algorithm: a study of scalabilityJoaquín Derrac, Salvador García, Francisco Herrera. memetic, 2(3):183-199, 2010. [doi]

A Survey on the Application of Genetic Programming to ClassificationPedro G. Espejo, Sebastián Ventura, Francisco Herrera. tsmc, 40(2):121-144, 2010. [doi]

Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise LearningAlberto Fernández, María José del Jesús, Francisco Herrera. ipmu 2010: 89-98 [doi]

Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative StudyAlberto Fernández, Salvador García, Julián Luengo, Ester Bernadó-Mansilla, Francisco Herrera. tec, 14(6):913-941, 2010. [doi]

On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-setsAlberto Fernández, María José del Jesús, Francisco Herrera. isci, 180(8):1268-1291, 2010. [doi]

Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relationsAlberto Fernández, María Calderón, Edurne Barrenechea Tartas, Humberto Bustince Sola, Francisco Herrera. fss, 161(23):3064-3080, 2010. [doi]

Integration of an Index to Preserve the Semantic Interpretability in the Multiobjective Evolutionary Rule Selection and Tuning of Linguistic Fuzzy SystemsMaría José Gacto, Rafael Alcalá, Francisco Herrera. tfs, 18(3):515-531, 2010. [doi]

Analysis of the Performance of a Semantic Interpretability-Based Tuning and Rule Selection of Fuzzy Rule-Based Systems by Means of a Multi-Objective Evolutionary AlgorithmMaría José Gacto, Rafael Alcalá, Francisco Herrera. ieaaie 2010: 228-238 [doi]

Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010, Proceedings, Part IIINicolás García-Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, Moonis Ali, editors, Volume 6098 of Lecture Notes in Computer Science, Springer, 2010. [doi]

Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010, Proceedings, Part INicolás García-Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, Moonis Ali, editors, Volume 6096 of Lecture Notes in Computer Science, Springer, 2010. [doi]

Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Cordoba, Spain, June 1-4, 2010, Proceedings, Part IINicolás García-Pedrajas, Francisco Herrera, Colin Fyfe, José Manuel Benítez, Moonis Ali, editors, Volume 6097 of Lecture Notes in Computer Science, Springer, 2010. [doi]

A Preliminary Study on the Selection of Generalized Instances for Imbalanced ClassificationSalvador García, Joaquín Derrac, Isaac Triguero, Cristóbal J. Carmona, Francisco Herrera. ieaaie 2010: 601-610 [doi]

A Review on Evolutionary Prototype SelectionSalvador García, José Ramón Cano, Francisco Herrera. In Raymond Chiong, editor, Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications. pages 92-113, IGI Global, 2010. [doi]

Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of powerSalvador García, Alberto Fernández, Julián Luengo, Francisco Herrera. isci, 180(10):2044-2064, 2010. [doi]

Guest Editors IntroductionFrancisco Herrera, Francesco Marcelloni, Vincenzo Loia. ijufks, 18(4), 2010. [doi]

A first approach for cost-sensitive classification with linguistic Genetic Fuzzy Systems in imbalanced data-setsVictoria Lopez, Alberto Fernández, Francisco Herrera. isda 2010: 676-681 [doi]

A study on the use of imputation methods for experimentation with Radial Basis Function Network classifiers handling missing attribute values: The good synergy between RBFNs and EventCovering methodJulián Luengo, Salvador García, Francisco Herrera. NN, 23(3):406-418, 2010. [doi]

Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning methodJulián Luengo, Francisco Herrera. fss, 161(1):3-19, 2010. [doi]

A bibliometric study about the research based on hybridating the fuzzy logic field and the other computational intelligent techniques: A visual approachAntonio Gabriel LÃ³pez-Herrera, M. J. Cobo, Enrique Herrera-Viedma, Francisco Herrera. ijhis, 7(1):17-32, 2010. [doi]

MA-SW-Chains: Memetic algorithm based on local search chains for large scale continuous global optimizationDaniel Molina, Manuel Lozano, Francisco Herrera. cec 2010: 1-8 [doi]

Memetic Algorithms for Continuous Optimisation Based on Local Search ChainsDaniel Molina, Manuel Lozano, Carlos García-Martínez, Francisco Herrera. ec, 18(1):27-63, 2010. [doi]

A preliminary study on overlapping and data fracture in imbalanced domains by means of Genetic Programming-based feature extractionJose G. Moreno-Torres, Francisco Herrera. isda 2010: 501-506 [doi]

Analysis of the efficacy of a Two-Stage methodology for ant colony optimization: Case of study with TSP and QAPAmilkar Puris, Rafael Bello, Francisco Herrera. eswa, 37(7):5443-5453, 2010. [doi]

On the Use of Distributed Genetic Algorithms for the Tuning of Fuzzy Rule Based-SystemsIgnacio Robles, Rafael Alcalá, José Manuel Benítez, Francisco Herrera. In Francisco Fernández de Vega, Erick Cantú-Paz, editors, Parallel and Distributed Computational Intelligence. Volume 269 of Studies in Computational Intelligence, pages 235-261, Springer, 2010. [doi]

Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuningJosé Antonio Sanz, Alberto Fernández, Humberto Bustince Sola, Francisco Herrera. isci, 180(19):3674-3685, 2010. [doi]

IPADE: Iterative Prototype Adjustment for Nearest Neighbor ClassificationIsaac Triguero, Salvador García, Francisco Herrera. tnn, 21(12):1984-1990, 2010. [doi]

A preliminary study on the use of differential evolution for adjusting the position of examples in nearest neighbor classificationIsaac Triguero, Salvador García, Francisco Herrera. cec 2010: 1-8 [doi]

A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-SetsPedro Villar, Alberto Fernández, Francisco Herrera. ipmu 2010: 741-750 [doi]

2009

KEEL: a software tool to assess evolutionary algorithms for data mining problemsJesús Alcalá-Fdez, Luciano Sánchez, Salvador García, María José del Jesús, Sebastián Ventura, Josep Maria Garrell i Guiu, José Otero, Cristóbal Romero, Jaume Bacardit, Víctor M. Rivas, Juan Carlos Fernández, Francisco Herrera. soco, 13(3):307-318, 2009. [doi]

A Multiobjective Evolutionary Approach to Concurrently Learn Rule and Data Bases of Linguistic Fuzzy-Rule-Based SystemsRafael Alcalá, Pietro Ducange, Francisco Herrera, Beatrice Lazzerini, Francesco Marcelloni. tfs, 17(5):1106-1122, 2009. [doi]

Learning the membership function contexts for mining fuzzy association rules by using genetic algorithmsJesÃºs AlcalÃ¡-Fdez, Rafael AlcalÃ¡, MarÃa JosÃ© Gacto, Francisco Herrera. fss, 160(7):905-921, 2009. [doi]

Improving fuzzy logic controllers obtained by experts: a case study in HVAC systemsRafael AlcalÃ¡, JesÃºs AlcalÃ¡-Fdez, MarÃa JosÃ© Gacto, Francisco Herrera. apin, 31(1):15-30, 2009. [doi]

Group decision making with incomplete fuzzy linguistic preference relationsSergio Alonso, Francisco Javier Cabrerizo, Francisco Chiclana, Francisco Herrera, Enrique Herrera-Viedma. ijis, 24(2):201-222, 2009. [doi]

h-Index: A review focused in its variants, computation and standardization for different scientific fieldsSergio Alonso, Francisco Javier Cabrerizo, Enrique Herrera-Viedma, Francisco Herrera. joi, 3(4):273-289, 2009. [doi]

Individual and Social Strategies to Deal with Ignorance Situations in Multi-Person Decision MakingSergio Alonso, Enrique Herrera-Viedma, Francisco Chiclana, Francisco Herrera. ijitdm, 8(2):313-333, 2009. [doi]

Non-dominated Multi-objective Evolutionary Algorithm Based on Fuzzy Rules Extraction for Subgroup DiscoveryCristóbal J. Carmona, Pedro González, María José del Jesús, Francisco Herrera. HAIS 2009: 573-580 [doi]

Cardinal Consistency of Reciprocal Preference Relations: A Characterization of Multiplicative TransitivityFrancisco Chiclana, Enrique Herrera-Viedma, Sergio Alonso, Francisco Herrera. tfs, 17(1):14-23, 2009. [doi]

A First Study on the Use of Coevolutionary Algorithms for Instance and Feature SelectionJoaquín Derrac, Salvador García, Francisco Herrera. HAIS 2009: 557-564 [doi]

Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-Sets Using an Evolutionary Adaptive Inference SystemAlberto Fernández, María José del Jesús, Francisco Herrera. iwann 2009: 294-301 [doi]

Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-setsAlberto Fernández, María José del Jesús, Francisco Herrera. ijar, 50(3):561-577, 2009. [doi]

On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-setsAlberto FernÃ¡ndez, MarÃa JosÃ© del JesÃºs, Francisco Herrera. eswa, 36(6):9805-9812, 2009. [doi]

Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-SetsAlberto FernÃ¡ndez, Francisco JosÃ© Berlanga, MarÃa JosÃ© del JesÃºs, Francisco Herrera. eusflat 2009: 42-47 [doi]

Implementation and Integration of Algorithms into the KEEL Data-Mining Software ToolAlberto FernÃ¡ndez, JuliÃ¡n Luengo, JoaquÃn Derrac, JesÃºs AlcalÃ¡-Fdez, Francisco Herrera. ideal 2009: 562-569 [doi]

Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary AlgorithmMarÃa JosÃ© Gacto, Rafael AlcalÃ¡, Francisco Herrera. isda 2009: 109-114 [doi]

A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving InterpretabilityMarÃa JosÃ© Gacto, Rafael AlcalÃ¡, Francisco Herrera. eusflat 2009: 1146-1151 [doi]

Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systemsMarÃa JosÃ© Gacto, Rafael AlcalÃ¡, Francisco Herrera. soco, 13(5):419-436, 2009. [doi]

Diagnose Effective Evolutionary Prototype Selection Using an Overlapping MeasureSalvador GarcÃa, JosÃ© RamÃ³n Cano, Ester BernadÃ³-Mansilla, Francisco Herrera. ijprai, 23(8):1527-1548, 2009. [doi]

Evolutionary Undersampling for Classification with Imbalanced Datasets: Proposals and TaxonomySalvador GarcÃa, Francisco Herrera. ec, 17(3):275-306, 2009. [doi]

A study on the use of non-parametric tests for analyzing the evolutionary algorithms behaviour: a case study on the CEC 2005 Special Session on Real Parameter OptimizationSalvador GarcÃa, Daniel Molina, Manuel Lozano, Francisco Herrera. heuristics, 15(6):617-644, 2009. [doi]

Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problemsSalvador GarcÃa, Alberto FernÃ¡ndez, Francisco Herrera. asc, 9(4):1304-1314, 2009. [doi]

A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretabilitySalvador GarcÃa, Alberto FernÃ¡ndez, JuliÃ¡n Luengo, Francisco Herrera. soco, 13(10):959-977, 2009. [doi]

A First Approach to Nearest Hyperrectangle Selection by Evolutionary AlgorithmsSalvador GarcÃa, JoaquÃn Derrac, JuliÃ¡n Luengo, Francisco Herrera. isda 2009: 517-522 [doi]

Foundations of Computational Intelligence - Volume 2: Approximate ReasoningAboul Ella Hassanien, Ajith Abraham, Francisco Herrera, editors, Volume 202 of Studies in Computational Intelligence, Springer, 2009. [doi]

Computing with words in decision making: foundations, trends and prospectsFrancisco Herrera, Sergio Alonso, Francisco Chiclana, Enrique Herrera-Viedma. fodm, 8(4):337-364, 2009. [doi]

Computing with words and decision makingFrancisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, Francisco Chiclana. fodm, 8(4):323-324, 2009. [doi]

Domains of Competence of Artificial Neural Networks Using Measures of Separability of ClassesJulián Luengo, Francisco Herrera. iwann 2009: 81-88 [doi]

On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification SystemJuliÃ¡n Luengo, Francisco Herrera. eusflat 2009: 1027-1032 [doi]

Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5JuliÃ¡n Luengo, Alberto FernÃ¡ndez, Salvador GarcÃa, Francisco Herrera. isda 2009: 523-528 [doi]

A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric testsJuliÃ¡n Luengo, Salvador GarcÃa, Francisco Herrera. eswa, 36(4):7798-7808, 2009. [doi]

A study of the use of multi-objective evolutionary algorithms to learn Boolean queries: A comparative studyAntonio Gabriel LÃ³pez-Herrera, Enrique Herrera-Viedma, Francisco Herrera. jasis, 60(6):1192-1207, 2009. [doi]

Applying multi-objective evolutionary algorithms to the automatic learning of extended Boolean queries in fuzzy ordinal linguistic information retrieval systemsAntonio Gabriel LÃ³pez-Herrera, Enrique Herrera-Viedma, Francisco Herrera. fss, 160(15):2192-2205, 2009. [doi]

Linguistic decision making: Tools and applicationsLuis MartÃnez, Da Ruan, Francisco Herrera, Enrique Herrera-Viedma, Paul P. Wang. isci, 179(14):2297-2298, 2009. [doi]

A memetic algorithm using local search chaining forblack-box optimization benchmarking 2009 for noise free functionsDaniel Molina, Manuel Lozano, Francisco Herrera. gecco 2009: 2255-2262 [doi]

A memetic algorithm using local search chaining for black-box optimization benchmarking 2009 for noisy functionsDaniel Molina, Manuel Lozano, Francisco Herrera. gecco 2009: 2359-2366 [doi]

Study of the Influence of the Local Search Method in Memetic Algorithms for Large Scale Continuous Optimization ProblemsDaniel Molina, Manuel Lozano, Francisco Herrera. lion 2009: 221-234 [doi]

Memetic algorithm with Local search chaining for large scale continuous optimization problemsDaniel Molina, Manuel Lozano, Francisco Herrera. cec 2009: 830-837 [doi]

Memetic Algorithm with Local Search Chaining for Continuous Optimization Problems: A Scalability TestDaniel Molina, Manuel Lozano, Francisco Herrera. isda 2009: 1068-1073 [doi]

Evolutionary Extraction of Association Rules: A Preliminary Study on their EffectivenessNicolò Flugy Papè, Jesús Alcalá-Fdez, Andrea Bonarini, Francisco Herrera. HAIS 2009: 646-653 [doi]

A Preliminar Analysis of CO2RBFN in Imbalanced ProblemsM. Dolores Pérez-Godoy, Antonio Jesús Rivera Rivas, Alberto Fernández, María José del Jesús, Francisco Herrera. iwann 2009: 57-64 [doi]

Distributed Genetic Tuning of Fuzzy Rule-Based SystemsIgnacio Robles, Rafael AlcalÃ¡, JosÃ© Manuel BenÃtez, Francisco Herrera. eusflat 2009: 1740-1744 [doi]

Evolutionary parallel and gradually distributed lateral tuning of fuzzy rule-based systemsIgnacio Robles, Rafael Alcalá, José Manuel Benítez, Francisco Herrera. evi, 2(1-2):5-19, 2009. [doi]

A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-SetsJ. Sanz, Alberto Fernández, Humberto Bustince Sola, Francisco Herrera. HAIS 2009: 581-588 [doi]

Hybrid crossover operators with multiple descendents for real-coded genetic algorithms: Combining neighborhood-based crossover operatorsAna M. Sánchez, Manuel Lozano, Pedro Villar, Francisco Herrera. ijis, 24(5):540-567, 2009. [doi]

A fuzzy model to evaluate the suitability of installing an enterprise resource planning systemP. J. SÃ¡nchez, Luis MartÃnez, Carlos GarcÃa-MartÃnez, Francisco Herrera, Enrique Herrera-Viedma. isci, 179(14):2333-2341, 2009. [doi]

Special issue: Data mining and hybrid intelligent systemsFatos Xhafa, Francisco Herrera, Mario Köppen. ijhis, 6(2):67, 2009. [doi]

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