Mostrando 10 resultados de: 14
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(6)
2016 IEEE Congress on Evolutionary Computation, CEC 2016(2)
2014 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2014(1)
2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings(1)
GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference(1)
Área temáticas
Ciencias de la computación(8)
Programación informática, programas, datos, seguridad(4)
Análisis(2)
Matemáticas(2)
Métodos informáticos especiales(2)
Analysis and comparison of multi-objective evolutionary approaches on the multi-objective 1/0 unit commitment problem
Conference ObjectAbstract: In this paper, we analyze the behavior and compare the performance of three state-of-the-art Multi-oPalabras claves:Autores:Hernán E. Aguirre, Jacquin S., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusA Review of Features and Limitations of Existing Scalable Multiobjective Test Suites
ArticleAbstract: In multiobjective optimization, a scalable test problem is one that can be formulated for an arbitraPalabras claves:Evolutionary algorithms, many-objective optimization, scalable multiobjective test problemsAutores:Coello Coello C.A., Hernán E. Aguirre, Tanaka K., Zapotecas-Martínez S.Fuentes:scopusA refinement mechanism to improve particle swarm optimization
Conference ObjectAbstract: Due to its simplicity and effectiveness in solving many optimization problems, Particle Swarm OptimiPalabras claves:Hybrid algorithms, Local search mechanism, Particle Swarm OptimizationAutores:Hernán E. Aguirre, Tan W.R., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusApproaches for many-objective optimization: Analysis and comparison on MNK-landscapes
Conference ObjectAbstract: This work analyses the behavior and compares the performance of MOEA/D, IBEA using the binary additiPalabras claves:Autores:Hernán E. Aguirre, Liefooghe A., Tanaka K., Verel S., Zapotecas-Martínez S.Fuentes:scopusApproximating pareto set topology by cubic interpolation on bi-objective problems
Conference ObjectAbstract: Difficult Pareto set topology refers to multi-objective problems with geometries of the Pareto set sPalabras claves:Difficult Pareto set topology, evolutionary algorithm, Interpolation, multi-objective optimizationAutores:Derbel B., Hernán E. Aguirre, Liefooghe A., Marca Y., Tanaka K., Verel S., Zapotecas-Martínez S.Fuentes:scopusGenetic algorithm assisted by a SVM for feature selection in gait classification
Conference ObjectAbstract: Feature selection is considered an important step for gait pattern recognition. The task of a gait cPalabras claves:feature selection, Gait classification, genetic algorithm (GA), support vector machine (SVM)Autores:Akimoto Y., Hernán E. Aguirre, Tanaka K., Yeoh T.W., Zapotecas-Martínez S.Fuentes:scopusGeometric differential evolution in MOEA/D: A preliminary study
Conference ObjectAbstract: The multi-objective evolutionary algorithm based on decomposition (MOEA/D) is an aggregation-based aPalabras claves:Autores:Derbel B., Hernán E. Aguirre, Liefooghe A., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusGeometric particle swarm optimization for multi-objective optimization using decomposition
Conference ObjectAbstract: Multi-objective evolutionary algorithms (MOEAs) based on decomposition are aggregation-based algoritPalabras claves:Decomposition-based moeas, Multi-objective combinatorial optimization, Particle Swarm OptimizationAutores:Hernán E. Aguirre, Moraglio A., Tanaka K., Zapotecas-Martínez S.Fuentes:scopusFeature selection in gait classification using geometric PSO assisted by SVM
Conference ObjectAbstract: Gait recognition is used to identify individuals by the way they walk. Recent research in automatedPalabras claves:feature selection, Gait classification, Particle Swarm Optimization, SUPPORT VECTOR MACHINESAutores:Akimoto Y., Hernán E. Aguirre, Tanaka K., Yeoh T.W., Zapotecas-Martínez S.Fuentes:scopusOn the low-discrepancy sequences and their use in MOEA/D for high-dimensional objective spaces
Conference ObjectAbstract: In spite of the success of the multi-objective evolutionary algorithm based on decomposition (MOEA/DPalabras claves:Autores:Coello Coello C.A., Hernán E. Aguirre, Tanaka K., Zapotecas-Martínez S.Fuentes:scopus