Journals

  • 2017

  1. Yuliana Martínez, Leonardo Trujillo, Enrique Naredo and Pierrick Legrand. A Comparison of Fitness-Case Sampling Methods for Symbolic Regression with Genetic Programming. pages 201–212, Springer International Publishing, 2014. URL, DOI BibTeX

    @inbook{Martínez2014,
    	author = "Mart{\'i}nez, Yuliana and Trujillo, Leonardo and Naredo, Enrique and Legrand, Pierrick",
    	title = "A Comparison of Fitness-Case Sampling Methods for Symbolic Regression with Genetic Programming",
    	booktitle = "EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V",
    	year = 2014,
    	publisher = "Springer International Publishing",
    	address = "Cham",
    	pages = "201--212",
    	abstract = "The canonical approach towards fitness evaluation in Genetic Programming (GP) is to use a static training set to determine fitness, based on a cost function averaged over all fitness-cases. However, motivated by different goals, researchers have recently proposed several techniques that focus selective pressure on a subset of fitness-cases at each generation. These approaches can be described as fitness-case sampling techniques, where the training set is sampled, in some way, to determine fitness. This paper shows a comprehensive evaluation of some of the most recent sampling methods, using benchmark and real-world problems for symbolic regression. The algorithms considered here are Interleaved Sampling, Random Interleaved Sampling, Lexicase Selection and a new sampling technique is proposed called Keep-Worst Interleaved Sampling (KW-IS). The algorithms are extensively evaluated based on test performance, overfitting and bloat. Results suggest that sampling techniques can improve performance compared with standard GP. While on synthetic benchmarks the difference is slight or none at all, on real-world problems the differences are substantial. Some of the best results were achieved by Lexicase Selection and Keep Worse-Interleaved Sampling. Results also show that on real-world problems overfitting correlates strongly with bloating. Furthermore, the sampling techniques provide efficiency, since they reduce the number of fitness-case evaluations required over an entire run.",
    	isbn = "978-3-319-07494-8",
    	doi = "10.1007/978-3-319-07494-8_14",
    	url = "https://doi.org/10.1007/978-3-319-07494-8_14"
    }
    

  1. Mauro Castelli, Raul Sormani, Leonardo Trujillo and Aleš Popovič. Predicting per capita violent crimes in urban areas: an artificial intelligence approach. Journal of Ambient Intelligence and Humanized Computing 8(1):29–36, February 2017. URL, DOI BibTeX

    @article{Castelli2017,
    	author = "Castelli, Mauro and Sormani, Raul and Trujillo, Leonardo and Popovi{\v{c}}, Ale{\v{s}}",
    	title = "Predicting per capita violent crimes in urban areas: an artificial intelligence approach",
    	journal = "Journal of Ambient Intelligence and Humanized Computing",
    	year = 2017,
    	month = "Feb",
    	day = 01,
    	volume = 8,
    	number = 1,
    	pages = "29--36",
    	abstract = "A major challenge facing all law-enforcement organizations is to accurately and efficiently analyze the growing volumes of crime data in order to extract useful knowledge for decision makers. This is an increasingly important task, considering the fast growth of urban populations in most countries. In particular, to reconcile urban growth with the need for security, a fundamental goal is to optimize the allocation of law enforcement resources. Moreover, optimal allocation can only be achieved if we can predict the incidence of crime within different urban areas. To answer this call, in this paper we propose an artificial intelligence system for predicting per capita violent crimes in urban areas starting from socio-economic data, law-enforcement data and other crime-related data obtained from different sources. The proposed framework blends a recently developed version of genetic programming that uses the concept of semantics during the search process with a local search method. To analyze the appropriateness of the proposed computational method for crime prediction, different urban areas of the United States have been considered. Experimental results confirm the suitability of the proposed method for addressing the problem at hand. In particular, the proposed method produces a lower error with respect to the existing state-of-the art techniques and it is particularly suitable for analyzing large amounts of data. This is an extremely important feature in a world that is currently moving towards the development of smart cities.",
    	issn = "1868-5145",
    	doi = "10.1007/s12652-015-0334-3",
    	url = "https://doi.org/10.1007/s12652-015-0334-3"
    }
    

  1. Josué Enríquez-Zárate, Leonardo Trujillo, Salvador Lara, Mauro Castelli, Emigdio Z-Flores, Luis Muñoz and Aleš Popovič. Automatic modeling of a gas turbine using genetic programming: An experimental study. Applied Soft Computing 50(Supplement C):212 - 222, 2017. URL, DOI BibTeX

    @article{ENRIQUEZZARATE2017212,
    	title = "Automatic modeling of a gas turbine using genetic programming: An experimental study",
    	journal = "Applied Soft Computing",
    	volume = 50,
    	number = "Supplement C",
    	pages = "212 - 222",
    	year = 2017,
    	issn = "1568-4946",
    	doi = "https://doi.org/10.1016/j.asoc.2016.11.019",
    	url = "http://www.sciencedirect.com/science/article/pii/S1568494616305889",
    	author = "Josué Enríquez-Zárate and Leonardo Trujillo and Salvador de Lara and Mauro Castelli and Emigdio Z-Flores and Luis Muñoz and Aleš Popovič",
    	keywords = "Gas turbine, Data-driven modeling, Genetic programming, Local search"
    }
    

  1. Juan Carlos Dibene, Yazmin Maldonado, Carlos Vera, Mauricio Oliveira, Leonardo Trujillo and Oliver Schütze. Optimizing the location of ambulances in Tijuana, Mexico. Computers in Biology and Medicine 80(Supplement C):107 - 115, 2017. URL, DOI BibTeX

    @article{DIBENE2017107,
    	title = "Optimizing the location of ambulances in Tijuana, Mexico",
    	journal = "Computers in Biology and Medicine",
    	volume = 80,
    	number = "Supplement C",
    	pages = "107 - 115",
    	year = 2017,
    	issn = "0010-4825",
    	doi = "https://doi.org/10.1016/j.compbiomed.2016.11.016",
    	url = "http://www.sciencedirect.com/science/article/pii/S0010482516303109",
    	author = "Juan Carlos Dibene and Yazmin Maldonado and Carlos Vera and Mauricio de Oliveira and Leonardo Trujillo and Oliver Schütze",
    	keywords = "Emergency Medical Services, Ambulance Location Problem, Optimization, Double Coverage Models, Integer Programming"
    }
    

  1. Mauro Castelli, Leonardo Trujillo, I Gonçalves and A Popovič. An evolutionary system for the prediction of high performance concrete strength based on semantic genetic programming. 19:651-658, June 2017. BibTeX

    @article{article,
    	author = "Castelli, Mauro and Trujillo, Leonardo and Gonçalves, I and Popovič, A",
    	year = 2017,
    	month = 06,
    	pages = "651-658",
    	title = "An evolutionary system for the prediction of high performance concrete strength based on semantic genetic programming",
    	volume = 19,
    	booktitle = "Computers and Concrete"
    }
    

  1. Enrique Naredo, Paulo Urbano and Leonardo Trujillo. The training set and generalization in grammatical evolution for autonomous agent navigation. Soft Computing 21(15):4399–4416, August 2017. URL, DOI BibTeX

    @article{Naredo2017,
    	author = "Naredo, Enrique and Urbano, Paulo and Trujillo, Leonardo",
    	title = "The training set and generalization in grammatical evolution for autonomous agent navigation",
    	journal = "Soft Computing",
    	year = 2017,
    	month = "Aug",
    	day = 01,
    	volume = 21,
    	number = 15,
    	pages = "4399--4416",
    	abstract = "Over recent years, evolutionary computation research has begun to emphasize the issue of generalization. Instead of evolving solutions that are optimized for a particular problem instance, the goal is to evolve solutions that can generalize to various different scenarios. This paper compares objective-based search and novelty search on a set of generalization oriented experiments for a navigation task using grammatical evolution (GE). In particular, this paper studies the impact that the training set has on the generalization of evolved solutions, considering: (1) the training set size; (2) the manner in which the training set is chosen (random or manual); and (3) if the training set is fixed throughout the run or dynamically changed every generation. Experimental results suggest that novelty search outperforms objective-based search in terms of evolving navigation behaviors that are able to cope with different initial conditions. The traditional objective-based search requires larger training sets and its performance degrades when the training set is not fixed. On the other hand, novelty search seems to be robust to different training sets, finding general solutions in almost all of the studied conditions with almost perfect generalization in many scenarios.",
    	issn = "1433-7479",
    	doi = "10.1007/s00500-016-2072-7",
    	url = "https://doi.org/10.1007/s00500-016-2072-7"
    }
    

  1. Darian Reyes Fernández de Bulnes. High-Level Synthesis through metaheuristics and LUTs optimization in FPGA devices. ISSN: 0921-7126. 30:151-168, May 2017. BibTeX

    @article{article,
    	author = "Reyes Fernández de Bulnes, Darian",
    	year = 2017,
    	month = 05,
    	pages = "151-168",
    	title = "High-Level Synthesis through metaheuristics and LUTs optimization in FPGA devices. ISSN: 0921-7126",
    	volume = 30,
    	booktitle = "Ai Communications"
    }
    

  1. Emigdio Z-Flores, Mohamed Abatal, Ali Bassam, Leonardo Trujillo, Perla Juárez-Smith and Youness El Hamzaoui. Modeling the adsorption of phenols and nitrophenols by activated carbon using genetic programming. Journal of Cleaner Production 161(Supplement C):860 - 870, 2017. URL, DOI BibTeX

    @article{ZFLORES2017860,
    	title = "Modeling the adsorption of phenols and nitrophenols by activated carbon using genetic programming",
    	journal = "Journal of Cleaner Production",
    	volume = 161,
    	number = "Supplement C",
    	pages = "860 - 870",
    	year = 2017,
    	issn = "0959-6526",
    	doi = "https://doi.org/10.1016/j.jclepro.2017.05.192",
    	url = "http://www.sciencedirect.com/science/article/pii/S0959652617311393",
    	author = "Emigdio Z-Flores and Mohamed Abatal and Ali Bassam and Leonardo Trujillo and Perla Juárez-Smith and Youness El Hamzaoui",
    	keywords = "Water treatment, Activated carbon, Phenols adsorption, Genetic programming, Regression"
    }
    

  1. Paul J Campos, Luis N Coria and Leonardo Trujillo. Nonlinear speed sensorless control of a surface-mounted PMSM based on a Thau observer. Electrical Engineering, December 2016. URL, DOI BibTeX

    @article{Campos2016,
    	author = "Campos, Paul J. and Coria, Luis N. and Trujillo, Leonardo",
    	title = "Nonlinear speed sensorless control of a surface-mounted PMSM based on a Thau observer",
    	journal = "Electrical Engineering",
    	year = 2016,
    	month = "Dec",
    	day = 01,
    	abstract = "This paper presents an alternative to solve the speed sensorless control of a surface-mounted synchronous motor based on localization of compact invariant sets (LCIS) and the Thau observer. Through the LCIS, the domain of attraction of the system dynamics is analyzed, allowing to obtain global knowledge about its operational bounds and its associated Lipschitz constant. Necessary and sufficient conditions for existence of a stable observer are fulfilled by two inequalities, providing two different sets of stability conditions and, as a consequence, two observers are proposed. The observer design is based on the availability of stator currents for measurement and stator voltages for feedback in a rotating reference frame. The designed observers are able to work in a wide speed range and also estimate rotor position accurately, even at low speed and zero-crossing speed. Simulations demonstrate that the observers can estimate both rotor speed and position. Additionally, the observers are experimentally validated with the Technosoft {\$}{\$}^{\{}{\backslash}textregistered {\}}{\$}{\$} ® MCK28335 platform. Results show that the observers can solve sensorless problem in a real-world scenario.",
    	issn = "1432-0487",
    	doi = "10.1007/s00202-016-0491-1",
    	url = "https://doi.org/10.1007/s00202-016-0491-1"
    }
    

  1. Mauro Castelli, Leonardo Vanneschi, Leonardo Trujillo and Aleš Popovič. Stock index return forecasting: Semantics-based genetic programming with local search optimiser. 10:159, January 2017. BibTeX

    @article{article,
    	author = "Castelli, Mauro and Vanneschi, Leonardo and Trujillo, Leonardo and Popovič, Aleš",
    	year = 2017,
    	month = 01,
    	pages = 159,
    	title = "Stock index return forecasting: Semantics-based genetic programming with local search optimiser",
    	volume = 10,
    	booktitle = "International Journal of Bio-Inspired Computation"
    }
    

  • 2016

  1. Yuliana Martínez, Leonardo Trujillo, Pierrick Legrand and Edgar Galván-López. Prediction of expected performance for a genetic programming classifier. Genetic Programming and Evolvable Machines 17(4):409–449, December 2016. URL, DOI BibTeX

    @article{Martínez2016,
    	author = "Mart{\'i}nez, Yuliana and Trujillo, Leonardo and Legrand, Pierrick and Galv{\'a}n-L{\'o}pez, Edgar",
    	title = "Prediction of expected performance for a genetic programming classifier",
    	journal = "Genetic Programming and Evolvable Machines",
    	year = 2016,
    	month = "Dec",
    	day = 01,
    	volume = 17,
    	number = 4,
    	pages = "409--449",
    	abstract = "The estimation of problem difficulty is an open issue in genetic programming (GP). The goal of this work is to generate models that predict the expected performance of a GP-based classifier when it is applied to an unseen task. Classification problems are described using domain-specific features, some of which are proposed in this work, and these features are given as input to the predictive models. These models are referred to as predictors of expected performance. We extend this approach by using an ensemble of specialized predictors (SPEP), dividing classification problems into groups and choosing the corresponding SPEP. The proposed predictors are trained using 2D synthetic classification problems with balanced datasets. The models are then used to predict the performance of the GP classifier on unseen real-world datasets that are multidimensional and imbalanced. This work is the first to provide a performance prediction of a GP system on test data, while previous works focused on predicting training performance. Accurate predictive models are generated by posing a symbolic regression task and solving it with GP. These results are achieved by using highly descriptive features and including a dimensionality reduction stage that simplifies the learning and testing process. The proposed approach could be extended to other classification algorithms and used as the basis of an expert system for algorithm selection.",
    	issn = "1573-7632",
    	doi = "10.1007/s10710-016-9265-9",
    	url = "https://doi.org/10.1007/s10710-016-9265-9"
    }
    

  1. Francisco Chávez, Francisco Fernández, Daniel Lanza, César Benavides, Juan Villegas, Leonardo Trujillo, Gustavo Olague and Graciela Román. Deploying massive runs of evolutionary algorithms with ECJ and Hadoop: Reducing interest points required for face recognition. The International Journal of High Performance Computing Applications 0(0):1094342016678302, 0. URL, DOI BibTeX

    @article{doi:10.1177/1094342016678302,
    	author = "Francisco Chávez and Francisco Fernández and Daniel Lanza and César Benavides and Juan Villegas and Leonardo Trujillo and Gustavo Olague and Graciela Román",
    	title = "Deploying massive runs of evolutionary algorithms with ECJ and Hadoop: Reducing interest points required for face recognition",
    	journal = "The International Journal of High Performance Computing Applications",
    	volume = 0,
    	number = 0,
    	pages = 1094342016678302,
    	year = 0,
    	doi = "10.1177/1094342016678302",
    	url = "https://doi.org/10.1177/1094342016678302",
    	eprint = "https://doi.org/10.1177/1094342016678302",
    	abstract = "In this paper we present a new strategy for deploying massive runs of evolutionary algorithms with the well-known Evolutionary Computation Library (ECJ) tool, which we combine with the MapReduce model so as to allow the deployment of computing intensive runs of evolutionary algorithms on big data infrastructures. Moreover, by addressing a hard real life problem, we show how the new strategy allows us to address problems that cannot be solved with more traditional approaches. Thus, this paper shows that by using the Hadoop framework ECJ users can, by means of a new parameter, choose where the run will be launched, whether in a Hadoop based infrastructure or in a desktop computer. Moreover, together with the performed tests we address the well-known face recognition problem with a new purpose: to allow a genetic algorithm to decide which are the more relevant interest points within the human face. Massive runs have allowed us to reduce the set from about 60 to just 20 points. In this way, recognition tasks based on the solution provided by the genetic algorithm will work significantly quicker in the future, given that just 20 points will be required. Therefore, two goals have been achieved: (a) to allow ECJ users to launch massive runs of evolutionary algorithms on big data infrastructures and also (b) to demonstrate the capabilities of the tool to successfully improve results regarding the problem of face recognition."
    }
    

  1. Mauro Castelli, Ivo Gonçalves, Leonardo Trujillo and Aleš Popovič. An evolutionary system for ozone concentration forecasting. Information Systems Frontiers 19(5):1123–1132, October 2017. URL, DOI BibTeX

    @article{Castelli2017,
    	author = "Castelli, Mauro and Gon{\c{c}}alves, Ivo and Trujillo, Leonardo and Popovi{\v{c}}, Ale{\v{s}}",
    	title = "An evolutionary system for ozone concentration forecasting",
    	journal = "Information Systems Frontiers",
    	year = 2017,
    	month = "Oct",
    	day = 01,
    	volume = 19,
    	number = 5,
    	pages = "1123--1132",
    	abstract = "Nowadays, with more than 50 {\%} of the world's population living in urban areas, cities are facing important environmental challenges. Among them, air pollution has emerged as one of the most important concerns, taking into account the social costs related to the effect of polluted air. According to a report of the World Health Organization, approximately seven million people die each year from the effects of air pollution. Despite this fact, the same report suggests that cities could greatly improve their air quality through local measures by exploiting modern and efficient solutions for smart infrastructures. Ideally, this approach requires insights of how pollutant levels change over time in specific locations. To tackle this problem, we present an evolutionary system for the prediction of pollutants levels based on a recently proposed variant of genetic programming. This system is designed to predict the amount of ozone level, based on the concentration of other pollutants collected by sensors disposed in critical areas of a city. An analysis of data related to the region of Yuen Long (one of the most polluted areas of China), shows the suitability of the proposed system for addressing the problem at hand. In particular, the system is able to predict the ozone level with greater accuracy with respect to other techniques that are commonly used to tackle similar forecasting problems.",
    	issn = "1572-9419",
    	doi = "10.1007/s10796-016-9706-2",
    	url = "https://doi.org/10.1007/s10796-016-9706-2"
    }
    

  1. Enrique N., Miguel Aurelio D., Manuel Jesús G., Carlos E V., Leonardo T. and Oscar S S.. Novelty Search for the Synthesis of Current Followers. Computación y Sistemas 20:609-621, 2016. URL BibTeX

    @article{ 61549258004,
    	author = "N., Enrique and D., Miguel Aurelio and G., Manuel de Jesús and V., Carlos E. and T., Leonardo and S., Oscar S.",
    	title = "Novelty Search for the Synthesis of Current Followers",
    	year = 2016,
    	journal = "Computación y Sistemas",
    	volume = 20,
    	pages = "609-621",
    	keywords = "Evolutionary electronics; circuit synthesis; current follower; novelty search.;",
    	issn = "1405-5546",
    	language = "Inglés",
    	url = "http://www.redalyc.org/articulo.oa?id=61549258004",
    	abstract = "A topology synthesis method is introduced using genetic algorithms (GA) based on novelty search (NS). NS is an emerging meta-heuristic, that guides the search based on the novelty of each solution instead of the objective function. The synthesized topologies are current follower (CF) circuits; these topologies are new and designed using integrated circuit CMOS technology of 0.35  m. Topologies are coded using a chromosome divided into four genes: small signal gene (SS), MOSFET synthesis gene (SMos), polarization gene (Bias) and current source synthesis gene (CM). The proposed synthesis method is coded in MatLab and uses SPICE to evaluate the CFs fitness. The GA based on NS (GA-NS) is compared with a standard objective-based GA, showing unique search dynamics and improved performance. Experimental results show twelve CFs synthesized by the GA-NS algorithm, and their main attributes are summarized and discussed. This work is the first to show that NS can be used as a promising alternative in the field of automatic circuit synthesis."
    }
    

  1. Víctor R L., Leonardo T., Pierrick L., Victor H D. and Gustavo O.. Comparison of Local Feature Extraction Paradigms Applied to Visual SLAM. Computación y Sistemas 20:565-587, 2016. URL BibTeX

    @article{ 61549258002,
    	author = "L., Víctor R. and T., Leonardo and L., Pierrick and D., Victor H. and O., Gustavo",
    	title = "Comparison of Local Feature Extraction Paradigms Applied to Visual SLAM",
    	year = 2016,
    	journal = "Computación y Sistemas",
    	volume = 20,
    	pages = "565-587",
    	keywords = "Local features; genetic programming; composite correlation filter; SLAM.;",
    	issn = "1405-5546",
    	language = "Inglés",
    	url = "http://www.redalyc.org/articulo.oa?id=61549258002",
    	abstract = "The detection and description of locally salient regions is one of the most widely used low-level processes in modern computer vision systems. The general approach relies on the detection of stable and invariant image features that can be uniquely charac- terized using compact descriptors. Many detection and description algorithms have been proposed, most of them derived using different assumptions or problem models. This work presents a comparison of different approaches towards the feature extraction problem, namely: (1) standard computer vision techniques; (2) automatic synthesis techniques based on genetic programming (GP); and (3) a new local descriptor based on composite correlation filtering, proposed for the first time in this paper. The considered methods are evaluated on a difficult real-world problem, vision-based simultaneous localization and mapping (SLAM). Using three experimental scenarios, results indicate that the GP-based methods and the correlation filtering techniques outperform widely used computer vision algorithms such as the Harris and Shi-Tomasi detectors and the Speeded Up Robust Features descriptor."
    }
    

  1. Enrique Naredo, Leonardo Trujillo, Pierrick Legrand, Sara Silva and Luis Muñoz. Evolving genetic programming classifiers with novelty search. Information Sciences 369(Supplement C):347 - 367, 2016. URL, DOI BibTeX

    @article{NAREDO2016347,
    	title = "Evolving genetic programming classifiers with novelty search",
    	journal = "Information Sciences",
    	volume = 369,
    	number = "Supplement C",
    	pages = "347 - 367",
    	year = 2016,
    	issn = "0020-0255",
    	doi = "https://doi.org/10.1016/j.ins.2016.06.044",
    	url = "http://www.sciencedirect.com/science/article/pii/S002002551630473X",
    	author = "Enrique Naredo and Leonardo Trujillo and Pierrick Legrand and Sara Silva and Luis Muñoz",
    	keywords = "Novelty search, Behavior-based Search, Supervised classification, Bloat"
    }
    

  1. Emigdio Z-Flores, Leonardo Trujillo, Arturo Sotelo, Pierrick Legrand and Luis N Coria. Regularity and Matching Pursuit feature extraction for the detection of epileptic seizures. Journal of Neuroscience Methods 266(Supplement C):107 - 125, 2016. URL, DOI BibTeX

    @article{ZFLORES2016107,
    	title = "Regularity and Matching Pursuit feature extraction for the detection of epileptic seizures",
    	journal = "Journal of Neuroscience Methods",
    	volume = 266,
    	number = "Supplement C",
    	pages = "107 - 125",
    	year = 2016,
    	issn = "0165-0270",
    	doi = "https://doi.org/10.1016/j.jneumeth.2016.03.024",
    	url = "http://www.sciencedirect.com/science/article/pii/S0165027016300309",
    	author = "Emigdio Z-Flores and Leonardo Trujillo and Arturo Sotelo and Pierrick Legrand and Luis N. Coria",
    	keywords = "Epilepsy detection, Hölderian regularity, Matching Pursuit, EEG classification"
    }
    

  1. Mauro Castelli, Leonardo Trujillo, Leonardo Vanneschi and Aleš Popovič. Prediction of relative position of CT slices using a computational intelligence system. Applied Soft Computing 46(Supplement C):537 - 542, 2016. URL, DOI BibTeX

    @article{CASTELLI2016537,
    	title = "Prediction of relative position of CT slices using a computational intelligence system",
    	journal = "Applied Soft Computing",
    	volume = 46,
    	number = "Supplement C",
    	pages = "537 - 542",
    	year = 2016,
    	issn = "1568-4946",
    	doi = "https://doi.org/10.1016/j.asoc.2015.09.021",
    	url = "http://www.sciencedirect.com/science/article/pii/S1568494615005931",
    	author = "Mauro Castelli and Leonardo Trujillo and Leonardo Vanneschi and Aleš Popovič",
    	keywords = "Computerized tomography, Radiology, Genetic programming, Semantics, Local search"
    }
    

  1. Leonardo Trujillo, Luis Muñoz, Edgar Galván-López and Sara Silva. neat Genetic Programming: Controlling bloat naturally. Information Sciences 333(Supplement C):21 - 43, 2016. URL, DOI BibTeX

    @article{TRUJILLO201621,
    	title = "neat Genetic Programming: Controlling bloat naturally",
    	journal = "Information Sciences",
    	volume = 333,
    	number = "Supplement C",
    	pages = "21 - 43",
    	year = 2016,
    	issn = "0020-0255",
    	doi = "https://doi.org/10.1016/j.ins.2015.11.010",
    	url = "http://www.sciencedirect.com/science/article/pii/S0020025515008038",
    	author = "Leonardo Trujillo and Luis Muñoz and Edgar Galván-López and Sara Silva",
    	keywords = "Genetic programming, Bloat, NeuroEvolution of augmenting topologies, Flat operator equalization"
    }
    

  • 2015

  1. Victor H Diaz-Ramirez, Andres Cuevas, Vitaly Kober, Leonardo Trujillo and Abdul Awwal. Pattern recognition with composite correlation filters designed with multi-objective combinatorial optimization. Optics Communications 338:77–89, 2015. URL, DOI BibTeX

    @article{Diaz-Ramirez2015,
    	author = "Diaz-Ramirez, Victor H. and Cuevas, Andres and Kober, Vitaly and Trujillo, Leonardo and Awwal, Abdul",
    	doi = "10.1016/j.optcom.2014.10.038",
    	file = ":home/emigdio/Documents/Mendeley Desktop/2015/Diaz-Ramirez et al. - 2015 - Pattern recognition with composite correlation filters designed with multi-objective combinatorial optimiza.pdf:pdf",
    	issn = 00304018,
    	journal = "Optics Communications",
    	keywords = "Combinatorial optimization,Composite correlation filters,Multi-objective evolutionary algorithm,Object recognition",
    	pages = "77--89",
    	publisher = "Elsevier",
    	title = "{Pattern recognition with composite correlation filters designed with multi-objective combinatorial optimization}",
    	url = "http://linkinghub.elsevier.com/retrieve/pii/S0030401814009547",
    	volume = 338,
    	year = 2015
    }
    

  1. Mario García-Valdez, Leonardo Trujillo, Juan-J Merelo, Francisco Fernández de Vega and Gustavo Olague. The EvoSpace Model for Pool-Based Evolutionary Algorithms. Journal of Grid Computing, pages 1-21, 2014. URL, DOI BibTeX

    @article{,
    	year = 2014,
    	issn = "1570-7873",
    	journal = "Journal of Grid Computing",
    	doi = "10.1007/s10723-014-9319-2",
    	title = "The EvoSpace Model for Pool-Based Evolutionary Algorithms",
    	url = "http://dx.doi.org/10.1007/s10723-014-9319-2",
    	publisher = "Springer Netherlands",
    	keywords = "Pool-based evolutionary algorithms; Distributed evolutionary algorithms; Heterogeneous computing platforms for bioinspired algorithms; Parameter setting",
    	author = "García-Valdez, Mario and Trujillo, Leonardo and Merelo, Juan-J and Fernández de Vega, Francisco and Olague, Gustavo",
    	pages = "1-21",
    	language = "English"
    }
    

  1. R C Gutiérrez-Urquídez, G Valencia-Palomo, O M Rodríguez-Elias and L Trujillo. Systematic selection of tuning parameters for efficient predictive controllers using a multiobjective evolutionary algorithm. Applied Soft Computing, pages 326 - 338, 2015. URL, DOI BibTeX

    @article{,
    	year = 2015,
    	issn = "1568-4946",
    	journal = "Applied Soft Computing",
    	doi = "http://dx.doi.org/10.1016/j.asoc.2015.02.033",
    	title = "Systematic selection of tuning parameters for efficient predictive controllers using a multiobjective evolutionary algorithm",
    	url = "http://www.sciencedirect.com/science/article/pii/S1568494615001349",
    	publisher = "Springer Netherlands",
    	author = "R.C. Guti\'{e}rrez-Urqu\'{i}dez and G. Valencia-Palomo and O.M. Rodr\'{i}guez-Elias and L. Trujillo",
    	pages = "326 - 338"
    }
    

  1. Arturo Sotelo, Enrique D Guijarro and Leonardo Trujillo. Seizure states identification in experimental epilepsy using gabor atom analysis. Journal of Neuroscience Methods 241(Complete):121-131, 2015. DOI BibTeX

    @article{,
    	affiliation = "Instituto Tecnolgico de Tijuana, Blvd. Industrial S/N, Tijuana, BC, Mexico; Universitat Politcnica de Valncia, Cami de Vera S/N, 46022 Valencia, Spain",
    	author = "Sotelo, Arturo and Guijarro, Enrique D. and Trujillo, Leonardo",
    	doi = "10.1016/j.jneumeth.2014.12.001",
    	journal = "Journal of Neuroscience Methods",
    	keywords = "Epilepsy; Seizure states; ECoG; Kindling model; Matching pursuit; Gabor atoms density",
    	language = "eng",
    	number = "Complete",
    	pages = "121-131",
    	title = "Seizure states identification in experimental epilepsy using gabor atom analysis",
    	volume = 241,
    	year = 2015
    }
    

  1. Mauro Castelli, Leonardo Trujillo, Leonardo Vanneschi and Aleš Popovič. Prediction of energy performance of residential buildings: A genetic programming approach. Energy and Buildings 102():67 - 74, 2015. URL, DOI BibTeX

    @article{,
    	title = "Prediction of energy performance of residential buildings: A genetic programming approach",
    	journal = "Energy and Buildings",
    	volume = 102,
    	number = "",
    	pages = "67 - 74",
    	year = 2015,
    	issn = "0378-7788",
    	doi = "http://dx.doi.org/10.1016/j.enbuild.2015.05.013",
    	url = "http://www.sciencedirect.com/science/article/pii/S0378778815003849",
    	author = "Mauro Castelli and Leonardo Trujillo and Leonardo Vanneschi and Aleš Popovič"
    }
    

  1. Mauro Castelli, Leonardo Trujillo and Leonardo Vanneschi. Energy Consumption Forecasting Using Semantic-based Genetic Programming with Local Search Optimizer. Intell. Neuroscience 2015:57:57–57:57, 2015. URL, DOI BibTeX

    @article{,
    	author = "Castelli, Mauro and Trujillo, Leonardo and Vanneschi, Leonardo",
    	title = "Energy Consumption Forecasting Using Semantic-based Genetic Programming with Local Search Optimizer",
    	journal = "Intell. Neuroscience",
    	issue_date = "January 2015",
    	volume = 2015,
    	month = "",
    	year = 2015,
    	issn = "1687-5265",
    	pages = "57:57--57:57",
    	articleno = 57,
    	numpages = 1,
    	url = "http://dx.doi.org/10.1155/2015/971908",
    	doi = "10.1155/2015/971908",
    	acmid = 2810687,
    	publisher = "Hindawi Publishing Corp.",
    	address = "New York, NY, United States"
    }
    

  1. Laurent Vézard, Pierrick Legrand, Marie Chavent, Frédérique Faïta-Aïnseba and Leonardo Trujillo. EEG Classification for the Detection of Mental States. Appl. Soft Comput. 32(C):113–131, 2015. URL, DOI BibTeX

    @article{,
    	author = {V\'{e}zard, Laurent and Legrand, Pierrick and Chavent, Marie and Fa\"{i}ta-A\"{i}nseba, Fr\'{e}d\'{e}rique and Trujillo, Leonardo},
    	title = "EEG Classification for the Detection of Mental States",
    	journal = "Appl. Soft Comput.",
    	issue_date = "July 2015",
    	volume = 32,
    	number = "C",
    	month = "",
    	year = 2015,
    	issn = "1568-4946",
    	pages = "113--131",
    	numpages = 19,
    	url = "http://dx.doi.org/10.1016/j.asoc.2015.03.028",
    	doi = "10.1016/j.asoc.2015.03.028",
    	acmid = 2778066,
    	publisher = "Elsevier Science Publishers B. V.",
    	address = "Amsterdam, The Netherlands, The Netherlands",
    	keywords = "Alertness, Common spatial pattern, Electroencephalographic signals, Genetic algorithm, Variable selection"
    }
    

  • 2013

  1. Arturo Sotelo, Enrique Guijarro, Leonardo Trujillo, Luis N Coria and Yuliana Martínez. Identification of epilepsy stages from ECoG using genetic programming classifiers. Computers in Biology and Medicine 43(11):1713 - 1723, 2013. URL, DOI BibTeX

    @article{,
    	title = "Identification of epilepsy stages from \{ECoG\} using genetic programming classifiers",
    	journal = "Computers in Biology and Medicine",
    	volume = 43,
    	number = 11,
    	pages = "1713 - 1723",
    	year = 2013,
    	doi = "http://dx.doi.org/10.1016/j.compbiomed.2013.08.016",
    	url = "http://www.sciencedirect.com/science/article/pii/S001048251300231X",
    	author = "Arturo Sotelo and Enrique Guijarro and Leonardo Trujillo and Luis N. Coria and Yuliana Mart\'{i}nez"
    }
    

  1. Francisco Fernández Vega, Gustavo Olague, Leonardo Trujillo and Daniel Lombraña Gonzalez. Customizable execution environments for evolutionary computation using BOINC + virtualization. Natural Computing 12(2):163-177, 2013. BibTeX

    @article{DBLP:journals/nc/VegaOTG13,
    	author = "Francisco Fern{\'a}ndez de Vega and Gustavo Olague and Leonardo Trujillo and Daniel Lombra{\~n}a Gonzalez",
    	title = "Customizable execution environments for evolutionary computation using BOINC + virtualization",
    	journal = "Natural Computing",
    	volume = 12,
    	number = 2,
    	year = 2013,
    	pages = "163-177",
    	ee = "http://dx.doi.org/10.1007/s11047-012-9343-8",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    

  1. José Parra, Leonardo Trujillo and Patricia Melin. Hybrid back-propagation training with evolutionary strategies. Soft Computing, pages 1-12, 2013. URL, DOI BibTeX

    @article{,
    	year = 2013,
    	issn = "1432-7643",
    	journal = "Soft Computing",
    	doi = "10.1007/s00500-013-1166-8",
    	title = "Hybrid back-propagation training with evolutionary strategies",
    	url = "http://dx.doi.org/10.1007/s00500-013-1166-8",
    	publisher = "Springer Berlin Heidelberg",
    	keywords = "Neural networks; Back-propagation; Evolutionary strategies",
    	author = "Parra, José and Trujillo, Leonardo and Melin, Patricia",
    	pages = "1-12",
    	language = "English"
    }
    

  • 2012

  1. Leonardo Trujillo, Pierrick Legrand, Gustavo Olague and Jacques Lévy Véhel. Evolving estimators of the pointwise Hölder exponent with Genetic Programming. Inf. Sci. 209:61-79, 2012. BibTeX

    @article{DBLP:journals/isci/TrujilloLOV12,
    	author = "Leonardo Trujillo and Pierrick Legrand and Gustavo Olague and Jacques L{\'e}vy V{\'e}hel",
    	title = {Evolving estimators of the pointwise H{\"o}lder exponent with Genetic Programming},
    	journal = "Inf. Sci.",
    	volume = 209,
    	year = 2012,
    	pages = "61-79",
    	ee = "http://dx.doi.org/10.1016/j.ins.2012.04.043",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    

  1. Gustavo Olague and Leonardo Trujillo. Interest point detection through multiobjective genetic programming. Appl. Soft Comput. 12(8):2566-2582, 2012. BibTeX

    @article{DBLP:journals/asc/OlagueT12,
    	author = "Gustavo Olague and Leonardo Trujillo",
    	title = "Interest point detection through multiobjective genetic programming",
    	journal = "Appl. Soft Comput.",
    	volume = 12,
    	number = 8,
    	year = 2012,
    	pages = "2566-2582",
    	ee = "http://dx.doi.org/10.1016/j.asoc.2012.03.058",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    

  1. Yuliana Martínez, Leonardo Trujillo, Galvan Galván-López and Pierrick Legrand. A comparison of predictive measures of problem difficulty for classification with Genetic Programming. In ERA 2012. 2012. BibTeX

    @inproceedings{,
    	title = "A comparison of predictive measures of problem difficulty for classification with Genetic Programming",
    	author = "Mart\'{i}nez, Yuliana and Trujillo, Leonardo and Galv\'{a}n-L\'{o}pez, Galvan and Legrand, Pierrick",
    	booktitle = "ERA 2012",
    	year = 2012
    }
    

  1. Sergio Pinto-Fernández, Alejandra Serrano-Trujillo, Trujillo Leonardo and Víctor H Díaz Ramírez. Reconocimiento facial robusto usando filtros de correlación diseñados a través de optimización combinatoria. In ERA 2012. 2012. BibTeX

    @inproceedings{trujillo2012comparison,
    	title = "Reconocimiento facial robusto usando filtros de correlaci\'{o}n dise\~{n}ados a trav\'{e}s de optimizaci\'{o}n combinatoria",
    	author = "Pinto-Fern\'{a}ndez, Sergio and Serrano-Trujillo, Alejandra and Leonardo, Trujillo and D\'{i}az Ram\'{i}rez, V\'{i}ctor H.",
    	booktitle = "ERA 2012",
    	year = 2012
    }
    

  • 2011

  1. Leonardo Trujillo, Gustavo Olague, Evelyne Lutton, Francisco Fernández Vega, León Dozal and Eddie Clemente. Speciation in Behavioral Space for Evolutionary Robotics. Journal of Intelligent and Robotic Systems 64(3-4):323-351, 2011. BibTeX

    @article{DBLP:journals/jirs/TrujilloOLVDC11,
    	author = "Leonardo Trujillo and Gustavo Olague and Evelyne Lutton and Francisco Fern{\'a}ndez de Vega and Le{\'o}n Dozal and Eddie Clemente",
    	title = "Speciation in Behavioral Space for Evolutionary Robotics",
    	journal = "Journal of Intelligent and Robotic Systems",
    	volume = 64,
    	number = "3-4",
    	year = 2011,
    	pages = "323-351",
    	ee = "http://dx.doi.org/10.1007/s10846-011-9542-z",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    

  1. Gustavo Olague and Leonardo Trujillo. Evolutionary-computer-assisted design of image operators that detect interest points using genetic programming. Image Vision Comput. 29(7):484-498, 2011. BibTeX

    @article{DBLP:journals/ivc/OlagueT11,
    	author = "Gustavo Olague and Leonardo Trujillo",
    	title = "Evolutionary-computer-assisted design of image operators that detect interest points using genetic programming",
    	journal = "Image Vision Comput.",
    	volume = 29,
    	number = 7,
    	year = 2011,
    	pages = "484-498",
    	ee = "http://dx.doi.org/10.1016/j.imavis.2011.03.004",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    

  1. Leonardo Trujillo. Genetic programming with one-point crossover and subtree mutation for effective problem solving and bloat control. Soft Comput. 15(8):1551-1567, 2011. BibTeX

    @article{DBLP:journals/soco/Trujillo11,
    	author = "Leonardo Trujillo",
    	title = "Genetic programming with one-point crossover and subtree mutation for effective problem solving and bloat control",
    	journal = "Soft Comput.",
    	volume = 15,
    	number = 8,
    	year = 2011,
    	pages = "1551-1567",
    	ee = "http://dx.doi.org/10.1007/s00500-010-0687-7",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    

  • 2010

  1. Mónica Beltrán, Patricia Melin and Leonardo Trujillo. Signature Recognition with a Hybrid Approach Combining Modular Neural Networks and Fuzzy Logic for Response Integration. pages 185–201, Springer Berlin Heidelberg, 2009. URL, DOI BibTeX

    @inbook{Beltrán2009,
    	author = "Beltr{\'a}n, M{\'o}nica and Melin, Patricia and Trujillo, Leonardo",
    	title = "Signature Recognition with a Hybrid Approach Combining Modular Neural Networks and Fuzzy Logic for Response Integration",
    	booktitle = "Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control",
    	year = 2009,
    	publisher = "Springer Berlin Heidelberg",
    	address = "Berlin, Heidelberg",
    	pages = "185--201",
    	abstract = "This chapter describes a modular neural network (MNN) with fuzzy integration for the problem of signature recognition. Currently, biometric identification has gained a great deal of research interest within the pattern recognition community. For instance, many attempts have been made in order to automate the process of identifying a person's handwritten signature; however this problem has proven to be a very difficult task. In this work, we propose a MNN that has three separate modules, each using different image features as input, these are: edges, wavelet coefficients, and the Hough transform matrix. Then, the outputs from each of these modules are combined using a Sugeno fuzzy integral and a fuzzy inference system. The experimental results obtained using a database of 30 individual's shows that the modular architecture can achieve a very high 99.33{\%} recognition accuracy with a test set of 150 images. Therefore, we conclude that the proposed architecture provides a suitable platform to build a signature recognition system. Furthermore we consider the verification of signatures as false acceptance, false rejection and error recognition of the MNN.",
    	isbn = "978-3-642-04514-1",
    	doi = "10.1007/978-3-642-04514-1_10",
    	url = "https://doi.org/10.1007/978-3-642-04514-1_10"
    }
    

  • 2009

  1. Mónica Beltrán, Patricia Melin and Leonardo Trujillo. Development of modular neural networks with fuzzy logic response integration for signature recognition. Fuzzy Information and Engineering 1(4):345-355, 2009. URL, DOI BibTeX

    @article{,
    	year = 2009,
    	issn = "1616-8658",
    	journal = "Fuzzy Information and Engineering",
    	volume = 1,
    	number = 4,
    	doi = "10.1007/s12543-009-0027-8",
    	title = "Development of modular neural networks with fuzzy logic response integration for signature recognition",
    	url = "http://dx.doi.org/10.1007/s12543-009-0027-8",
    	publisher = "Springer-Verlag",
    	keywords = "Modular neural networks; Fuzzy integration; Pattern recognition",
    	author = "Beltrán, Mónica and Melin, Patricia and Trujillo, Leonardo",
    	pages = "345-355",
    	language = "English"
    }
    

  • 2008

  1. Leonardo Trujillo and Gustavo Olague. Automated design of image operators that detect interest points. Evol. Comput. 16(4):483–507, 2008. URL, DOI BibTeX

    @article{Trujillo:2008:ADI:1479056.1479060,
    	author = "Trujillo, Leonardo and Olague, Gustavo",
    	title = "Automated design of image operators that detect interest points",
    	journal = "Evol. Comput.",
    	issue_date = "Winter 2008",
    	volume = 16,
    	number = 4,
    	month = "",
    	year = 2008,
    	issn = "1063-6560",
    	pages = "483--507",
    	numpages = 25,
    	url = "http://dx.doi.org/10.1162/evco.2008.16.4.483",
    	doi = "10.1162/evco.2008.16.4.483",
    	acmid = 1479060,
    	publisher = "MIT Press",
    	address = "Cambridge, MA, USA",
    	keywords = "Feature detection, computer vision, genetic programming, interest points"
    }
    

  • 2007

  1. Oscar Castillo, Leonardo Trujillo and Patricia Melin. Multiple Objective Genetic Algorithms for Path-planning Optimization in Autonomous Mobile Robots. Soft Comput. 11(3):269–279, 2006. URL, DOI BibTeX

    @article{Castillo:2006:MOG:1178398.1178406,
    	author = "Castillo, Oscar and Trujillo, Leonardo and Melin, Patricia",
    	title = "Multiple Objective Genetic Algorithms for Path-planning Optimization in Autonomous Mobile Robots",
    	journal = "Soft Comput.",
    	issue_date = "October 2006",
    	volume = 11,
    	number = 3,
    	month = "",
    	year = 2006,
    	issn = "1432-7643",
    	pages = "269--279",
    	numpages = 11,
    	url = "http://dx.doi.org/10.1007/s00500-006-0068-4",
    	doi = "10.1007/s00500-006-0068-4",
    	acmid = 1178406,
    	publisher = "Springer-Verlag",
    	address = "Berlin, Heidelberg",
    	keywords = "Autonomous robots, Genetic algorithms, Multiple objective optimization, Path planning"
    }
    

  1. Leonardo Trujillo, Gustavo Olague, Pierrick Legrand, Evelyne Lutton and others. A new regularity based descriptor computed from local image oscillations.. Optics Express 15(10):6140–6145, 2007. BibTeX

    @article{trujillo2007new,
    	title = "A new regularity based descriptor computed from local image oscillations.",
    	author = "Trujillo, Leonardo and Olague, Gustavo and Legrand, Pierrick and Lutton, Evelyne and others",
    	journal = "Optics Express",
    	volume = 15,
    	number = 10,
    	pages = "6140--6145",
    	year = 2007
    }
    

  1. Benjamín Hernández, Gustavo Olague, Riad I Hammoud, Leonardo Trujillo and Eva Romero. Visual learning of texture descriptors for facial expression recognition in thermal imagery. Computer Vision and Image Understanding 106(2-3):258-269, 2007. BibTeX

    @article{DBLP:journals/cviu/HernandezOHTR07,
    	author = "Benjam\'{i}n Hern\'{a}ndez and Gustavo Olague and Riad I. Hammoud and Leonardo Trujillo and Eva Romero",
    	title = "Visual learning of texture descriptors for facial expression recognition in thermal imagery",
    	journal = "Computer Vision and Image Understanding",
    	volume = 106,
    	number = "2-3",
    	year = 2007,
    	pages = "258-269",
    	ee = "http://dx.doi.org/10.1016/j.cviu.2006.08.012",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    

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