Extractive single-document summarization based on genetic operators and guided local search M Mendoza, S Bonilla, C Noguera, C Cobos, E León Expert Systems with Applications 41 (9), 4158-4169, 2014 | 162 | 2014 |
Clustering of web search results based on the cuckoo search algorithm and balanced Bayesian information criterion C Cobos, H Muñoz-Collazos, R Urbano-Muñoz, M Mendoza, E León, ... Information Sciences 281, 248-264, 2014 | 139 | 2014 |
A hybrid system of pedagogical pattern recommendations based on singular value decomposition and variable data attributes C Cobos, O Rodriguez, J Rivera, J Betancourt, M Mendoza, E León, ... Information Processing & Management 49 (3), 607-625, 2013 | 108 | 2013 |
Web document clustering based on global-best harmony search, K-means, frequent term sets and Bayesian information criterion C Cobos, J Andrade, W Constain, M Mendoza, E León IEEE congress on evolutionary computation, 1-8, 2010 | 49 | 2010 |
GHS+ LEM: global-best harmony search using learnable evolution models C Cobos, D Estupiñán, J Pérez Applied Mathematics and Computation 218 (6), 2558-2578, 2011 | 43 | 2011 |
Specification of mixed logit models assisted by an optimization framework A Paz, C Arteaga, C Cobos Journal of choice modelling 30, 50-60, 2019 | 37 | 2019 |
A multiobjective bilevel approach based on global-best harmony search for defining optimal routes and frequencies for bus rapid transit systems E Ruano-Daza, C Cobos, J Torres-Jimenez, M Mendoza, A Paz Applied Soft Computing 67, 567-583, 2018 | 35 | 2018 |
CMIN-a CRISP-DM-based case tool for supporting data mining projects C Cobos, J Zuñiga, J Guarin, E León, M Mendoza Ingeniería e Investigación 30 (3), 45-56, 2010 | 35* | 2010 |
Web document clustering based on a new niching memetic algorithm, term-document matrix and Bayesian information criterion C Cobos, C Montealegre, MF Mejía, M Mendoza, E León IEEE congress on evolutionary computation, 1-8, 2010 | 27 | 2010 |
A hyper-heuristic approach to design and tuning heuristic methods for web document clustering C Cobos, M Mendoza, E León 2011 IEEE Congress of Evolutionary Computation (CEC), 1350-1358, 2011 | 26 | 2011 |
Multi-objective memetic algorithm based on NSGA-II and simulated annealing for calibrating CORSIM micro-simulation models of vehicular traffic flow C Cobos, C Erazo, J Luna, M Mendoza, C Gaviria, C Arteaga, A Paz Lecture Notes in Computer Science 9868, 468-476, 2016 | 25 | 2016 |
Grouping of business processes models based on an incremental clustering algorithm using fuzzy similarity and multimodal search A Ordoñez, H Ordoñez, JC Corrales, C Cobos, LK Wives, LH Thom Expert Systems with Applications 67, 163-177, 2017 | 24 | 2017 |
A new memetic algorithm for multi-document summarization based on CHC algorithm and greedy search M Mendoza, C Cobos, E León, M Lozano, F Rodríguez, ... Lecture Notes in Computer Science 8856, 125-138, 2014 | 24 | 2014 |
Multidimensional analysis model for a document warehouse that includes textual measures M Mendoza, E Alegría, M Maca, C Cobos, E León Decision Support Systems 72, 44-59, 2015 | 23 | 2015 |
An impact study of business process models for requirements elicitation in XP H Ordóñez, AFE Villada, DLV Vanegas, C Cobos, A Ordóñez, R Segovia Computational Science and Its Applications--ICCSA 2015: 15th International …, 2015 | 23 | 2015 |
Metaheuristic algorithms for building Covering Arrays: A review JA Timaná-Peña, CA Cobos-Lozada, J Torres-Jimenez Revista Facultad de Ingeniería 25 (43), 31-45, 2016 | 22 | 2016 |
Framework for the Training of Deep Neural Networks in TensorFlow Using Metaheuristics J Muñoz-Ordóñez, C Cobos, M Mendoza, E Herrera-Viedma, F Herrera, ... Lecture Notes in Computer Science 11314, 801-811, 2018 | 20 | 2018 |
A harmony search algorithm for clustering with feature selection C Cobos, E León, M Mendoza Revista Facultad de Ingeniería, 153-164, 2010 | 20 | 2010 |
A Multi-objective Approach for the Calibration of Microscopic Traffic Flow Simulation Models C Cobos, A Paz, J Luna, C Erazo, M Mendoza IEEE Access 8, 103124-103140, 2020 | 19 | 2020 |
Modelo de machine learning para la predicción de las tendencias de hurto en Colombia H Ordóñez, C Cobos, V Bucheli Revista Ibérica de Sistemas e Tecnologias de Informação, 494-506, 2020 | 19 | 2020 |