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- Houssein, E.H., Hussain, K., Abualigah, L., ...Djenouri, Y., Cuevas, E.(2021). An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation. Knowledge-Based Systems. 229, 107348
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- Rodríguez, A., Camarena, O., Cuevas, E., Aranguren, I., Valdivia-G, A., Morales-Castañeda, B., Zaldívar, D., & Pérez-Cisneros, M. (2021). Group-based synchronous-asynchronous Grey Wolf Optimizer. Applied Mathematical Modelling, 93, 226–243. https://doi.org/10.1016/j.apm.2020.12.016
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- Morales-Castañeda, B., Zaldívar, D., Cuevas, E., Rodríguez, A., & Navarro, M. A. (2021). Population management in metaheuristic algorithms: Could less be more? Applied Soft Computing, 107, 107389. https://doi.org/10.1016/j.asoc.2021.107389
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- Avalos, O., Cuevas, E., Becerra, H. G., Gálvez, J., Hinojosa, S., & Zaldívar, D. (2021). Kernel Recursive Least Square Approach for Power System Harmonic Estimation. Electric Power Components and Systems, 1–16. https://doi.org/10.1080/15325008.2021.1908457
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- Abd Elaziz, M., Nabil, N., Moghdani, R., Ewees, A. A., Cuevas, E., & Lu, S. (2021). Multilevel thresholding image segmentation based on improved volleyball premier league algorithm using whale optimization algorithm. Multimedia Tools and Applications, 80(8), 12435–12468. https://doi.org/10.1007/s11042-020-10313-w
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- Luque-Chang, A., Cuevas, E., Pérez-Cisneros, M., Fausto, F., Valdivia-González, A., & Sarkar, R. (2021). Moth Swarm Algorithm for Image Contrast Enhancement. Knowledge-Based Systems, 212, 106607. https://doi.org/10.1016/j.knosys.2020.106607
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- Cuevas, E., Becerra, H., Escobar, H., Luque-Chang, A., Pérez, M., Eid, H. F., & Jiménez, M. (2021). Search Patterns Based on Trajectories Extracted from the Response of Second-Order Systems. Applied Sciences, 11(8), 3430. https://doi.org/10.3390/app11083430
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- Ibarra-Nuño, C., Rodríguez, A., Alejo-Reyes, A., Cuevas, E., Ramirez, J. M., Rosas-Caro, J. C., & Robles-Campos, H. R. (2021). Optimal Operation of the Voltage-Doubler Boost Converter through an Evolutionary Algorithm. Mathematics, 9(4), 423. https://doi.org/10.3390/math9040423
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- del Río, A. H., Aranguren, I., Oliva, D., Elaziz, M. A., & Cuevas, E. (2020). Efficient image segmentation through 2D histograms and an improved owl search algorithm. International Journal of Machine Learning and Cybernetics, 12(1), 131–150. https://doi.org/10.1007/s13042-020-01161-z
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- Rodríguez, A., Alejo-Reyes, A., Cuevas, E., Robles-Campos, H. R., & Rosas-Caro, J. C. (2020). Numerical Optimization of Switching Ripples in the Double Dual Boost Converter through the Evolutionary Algorithm L-SHADE. Mathematics, 8(11), 1911. https://doi.org/10.3390/math8111911
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- Cuevas, E., Gálvez, J., Avila, K., Toski, M., & Rafe, V. (2020). A new metaheuristic approach based on agent systems principles. Journal of Computational Science, 47, 101244. https://doi.org/10.1016/j.jocs.2020.101244
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- Ortega-Sánchez, N., Oliva, D., Cuevas, E., Pérez-Cisneros, M., & Juan, A. A. (2020). An Evolutionary Approach to Improve the Halftoning Process. Mathematics, 8(9), 1636. https://doi.org/10.3390/math8091636
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- Alejo-Reyes, A., Cuevas, E., Rodríguez, A., Mendoza, A., & Olivares-Benitez, E. (2020). An Improved Grey Wolf Optimizer for a Supplier Selection and Order Quantity Allocation Problem. Mathematics, 8(9), 1457. https://doi.org/10.3390/math8091457
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- Rodríguez, A., Cuevas, E., Zaldívar, D., Pérez-Cisneros, M., García-Gil, G., & Morales-Castañeda, B. (2020). An improved clustering method based on biological visual models. Applied Mathematical Modelling, 85, 174–191. https://doi.org/10.1016/j.apm.2020.04.008
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- Statistical Tree-based Population Seeding for Rolling Horizon EAs in General Video Game Playing (2020). E. López, O. Gorshkova, P. Mooney, Fred Valdez Ameneyro & E. C. Jiménez.
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- Cuevas, E., Trujillo, A., Navarro, M. A., & Diaz, P. (2020). Comparison of Recent Metaheuristic Algorithms for Shape Detection in Images. International Journal of Computational Intelligence Systems, 13(1), 1059. https://doi.org/10.2991/ijcis.d.200729.001
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- Rodríguez, A., Alejo-Reyes, A., Cuevas, E., Beltran-Carbajal, F., & Rosas-Caro, J. C. (2020). An Evolutionary Algorithm-Based PWM Strategy for a Hybrid Power Converter. Mathematics, 8(8), 1247. https://doi.org/10.3390/math8081247
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- Avalos, O., Cuevas, E., Gálvez, J., Houssein, E. H., & Hussain, K. (2020). Comparison of Circular Symmetric Low-Pass Digital IIR Filter Design Using Evolutionary Computation Techniques. Mathematics, 8(8), 1226. https://doi.org/10.3390/math8081226
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- Gálvez, J., Cuevas, E., & Gopal Dhal, K. (2020). A Competitive Memory Paradigm for Multimodal Optimization Driven by Clustering and Chaos. Mathematics, 8(6), 934. https://doi.org/10.3390/math8060934
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- Morales-Castañeda, B., Zaldívar, D., Cuevas, E., Fausto, F., & Rodríguez, A. (2020). A better balance in metaheuristic algorithms: Does it exist? Swarm and Evolutionary Computation, 54, 100671. https://doi.org/10.1016/j.swevo.2020.100671
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- Maciel C., O., Cuevas, E., Navarro, M. A., Zaldívar, D., & Hinojosa, S. (2020). Side-Blotched Lizard Algorithm: A polymorphic population approach. Applied Soft Computing, 88, 106039. https://doi.org/10.1016/j.asoc.2019.106039
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- editors: Erik Cuevas, G., Oliva, D., & Osuna, V. (2020). Special issue: Bio-inspired algorithms and Bio-systems. Mathematical Biosciences and Engineering, 17(3), 2400–2401. https://doi.org/10.3934/mbe.2020129
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- Fausto, F., Reyna-Orta, A., Cuevas, E., Andrade, N. G., & Perez-Cisneros, M. (2019). From ants to whales: metaheuristics for all tastes. Artificial Intelligence Review, 53(1), 753–810. https://doi.org/10.1007/s10462-018-09676-2
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- Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Pérez-Cisneros, M. (2019). Reducing overlapped pixels: a multi-objective color thresholding approach. Soft Computing, 24(9), 6787–6807. https://doi.org/10.1007/s00500-019-04315-6
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- Gálvez, J., Cuevas, E., Becerra, H., & Avalos, O. (2019). A hybrid optimization approach based on clustering and chaotic sequences. International Journal of Machine Learning and Cybernetics, 11(2), 359–401. https://doi.org/10.1007/s13042-019-00979-6
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- Cuevas, E., Rodríguez, A., Valdivia, A., Zaldívar, D., & Pérez, M. (2019). A hybrid evolutionary approach based on the invasive weed optimization and estimation distribution algorithms. Soft Computing, 23(24), 13627–13668. https://doi.org/10.1007/s00500-019-03902-x
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- Ibrahim, R. A., Elaziz, M. A., Oliva, D., Cuevas, E., & Lu, S. (2019). An opposition-based social spider optimization for feature selection. Soft Computing, 23(24), 13547–13567. https://doi.org/10.1007/s00500-019-03891-x
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- Morales-Castañeda, B., Zaldívar, D., Cuevas, E., Maciel-Castillo, O., Aranguren, I., & Fausto, F. (2019). An improved Simulated Annealing algorithm based on ancient metallurgy techniques. Applied Soft Computing, 84, 105761. https://doi.org/10.1016/j.asoc.2019.105761
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- Cuevas, E., & Galvez, J. (2019). An optimization algorithm guided by a machine learning approach. International Journal of Machine Learning and Cybernetics, 10(11), 2963–2991. https://doi.org/10.1007/s13042-018-00915-0
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- Maciel, O., Valdivia, A., Oliva, D., Cuevas, E., Zaldívar, D., & Pérez-Cisneros, M. (2019). A novel hybrid metaheuristic optimization method: hypercube natural aggregation algorithm. Soft Computing, 24(12), 8823–8856. https://doi.org/10.1007/s00500-019-04416-2
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- Rodríguez, A., Cuevas, E., Zaldivar, D., & Castañeda, L. (2019). Clustering with biological visual models. Physica A: Statistical Mechanics and its Applications, 528, 121505. https://doi.org/10.1016/j.physa.2019.121505
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- Cuevas, E., Díaz-Cortes, M. A., & Mezura-Montes, E. (2019). Corner detection of intensity images with cellular neural networks (CNN) and evolutionary techniques. Neurocomputing, 347, 82–93. https://doi.org/10.1016/j.neucom.2019.03.014
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- Fausto, F., Cuevas, E., Maciel-Castillo, O., & Morales-Castañeda, B. (2019). A Real-Coded Optimal Sensor Deployment Scheme for Wireless Sensor Networks Based on the Social Spider Optimization Algorithm. International Journal of Computational Intelligence Systems, 12(2), 676. https://doi.org/10.2991/ijcis.d.190614.001
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- Gálvez, J., Cuevas, E., Hinojosa, S., Avalos, O., & Pérez-Cisneros, M. (2019). A reactive model based on neighborhood consensus for continuous optimization. Expert Systems with Applications, 121, 115–141. https://doi.org/10.1016/j.eswa.2018.12.018
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- Avalos, O., Cuevas Jimenez, E. V., Valdivia-González, A., Gálvez, J., Hinojosa, S., Zaldívar, D., & Oliva, D. (2019). A Comparative Study of Evolutionary Computation Techniques for Solar Cells Parameter Estimation. Computación y Sistemas, 23(1). https://doi.org/10.13053/cys-23-1-2881
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- Zaldivar, D., Cuevas, E., Maciel, O., Valdivia, A., Chavolla, E., & Oliva, D. (2019). Learning classical and metaheuristic optimization techniques by using an educational platform based on LEGO robots. The International Journal of Electrical Engineering & Education, 58(2), 286–305. https://doi.org/10.1177/0020720918822738
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- Oliva, D., Hinojosa, S., Osuna-Enciso, V., Cuevas, E., Pérez-Cisneros, M., & Sanchez-Ante, G. (2019). Image segmentation by minimum cross entropy using evolutionary methods. Soft Computing, 23(2), 431–450. https://doi.org/10.1007/s00500-017-2794-1
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- Hinojosa, S., Dhal, K. G., Elaziz, M. A., Oliva, D., & Cuevas, E. (2018). Entropy-based imagery segmentation for breast histology using the stochastic fractal search. Neurocomputing, 321, 201-215.
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- Zaldivar, D., Morales, B., Rodriguez, A., Valdivia-G, A., Cuevas, E., & Perez-Cisneros, M. (2018). A novel bio-inspired optimization model based on Yellow Saddle Goatfish behavior. Biosystems, 174, 1-21.
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- Hinojosa, S., Avalos, O., Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Gálvez, J. (2018). Unassisted thresholding based on multi-objective evolutionary algorithms. Knowledge-Based Systems, 159, 221-232.
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- Cuevas, E., Enríquez, L., Zaldívar, D., & Pérez-Cisneros, M. (2018). A selection method for evolutionary algorithms based on the golden section. Expert Systems with Applications, 106, 183-196.
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- Díaz, P., Pérez-Cisneros, M., Cuevas, E., Camarena, O., Martinez, F. A. F., & González, A. (2018). A swarm approach for improving voltage profiles and reduce power loss on electrical distribution networks. IEEE Access, 6, 49498-49512.
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- Gálvez, J., Cuevas, E., Avalos, O., Oliva, D., & Hinojosa, S. (2018). Electromagnetism-like mechanism with collective animal behavior for multimodal optimization. Applied Intelligence, 48(9), 2580-2612.
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- Díaz-Cortés, M. A., Ortega-Sánchez, N., Hinojosa, S., Oliva, D., Cuevas, E., Rojas, R., & Demin, A. (2018). A multi-level thresholding method for breast thermograms analysis using Dragonfly algorithm. Infrared Physics & Technology, 93, 346-361.
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- Cuevas, E., Reyna-Orta, A., & Díaz-Cortes, M. A. (2018). A multimodal optimization algorithm inspired by the states of matter. Neural Processing Letters, 48(1), 517-556.
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- Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Avalos, O., & Gálvez, J. (2018). Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm. Neural Computing and Applications, 29(8), 319-335.
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- Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Avalos, O., & Gálvez, J. (2018). Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm. Neural Computing and Applications, 29(8), 319-335.
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- Díaz, P., Pérez-Cisneros, M., Cuevas, E., Avalos, O., Gálvez, J., Hinojosa, S., & Zaldivar, D. (2018). An improved crow search algorithm applied to energy problems. Energies, 11(3), 571.
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- Luque-Chang, A., Cuevas, E., Fausto, F., Zaldivar, D., & Pérez, M. (2018). Social spider optimization algorithm: modifications, applications, and perspectives. Mathematical Problems in Engineering, 2018.
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- Cuevas, E., Zaldívar, D., Pajares, G., Perez-Cisneros, M., & Rojas, R. (2013). Computational intelligence in image processing. Mathematical Problems in Engineering, 2013.
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- Cuevas, E., Díaz, P., Avalos, O., Zaldívar, D., & Pérez-Cisneros, M. (2018). Nonlinear system identification based on ANFIS-Hammerstein model using Gravitational search algorithm. Applied Intelligence, 48(1), 182-203.
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- Camarena, O., Cuevas, E., Pérez-Cisneros, M., Fausto, F., González, A., & Valdivia, A. (2018). Ls-II: An Improved Locust Search Algorithm for Solving Optimization Problems. Mathematical Problems in Engineering, 2018.
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- Díaz-Cortés, M. A., Cuevas, E., Gálvez, J., & Camarena, O. (2017). A new metaheuristic optimization methodology based on fuzzy logic. Applied Soft Computing, 61, 549-569.
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- González, A., Cuevas, E., Fausto, F., Valdivia, A., & Rojas, R. (2017). A template matching approach based on the behavior of swarms of locust. Applied Intelligence, 47(4), 1087-1098.
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- Fausto, F., Cuevas, E., & Gonzales, A. (2017). A new descriptor for image matching based on bionic principles. Pattern Analysis and Applications, 20(4), 1245-1259.
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- Fausto, F., Cuevas, E., Valdivia, A., & González, A. (2017). A global optimization algorithm inspired in the behavior of selfish herds. Biosystems, 160, 39-55.
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- Cuevas, E., Luque, A., Zaldívar, D., & Pérez-Cisneros, M. (2017). Evolutionary calibration of fractional fuzzy controllers. Applied Intelligence, 47(2), 291-303.
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- Oliva, D., Hinojosa, S., Cuevas, E., Pajares, G., Avalos, O., & Gálvez, J. (2017). Cross entropy based thresholding for magnetic resonance brain images using Crow Search Algorithm. Expert Systems with Applications, 79, 164-180.
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- Valdivia-González, A., Zaldívar, D., Cuevas, E., Pérez-Cisneros, M., Fausto, F., & González, A. (2017). A chaos-embedded gravitational search algorithm for the identification of electrical parameters of photovoltaic cells. Energies, 10(7), 1052.
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- Gurubel, K. J., Osuna-Enciso, V., Coronado-Mendoza, A., & Cuevas, E. (2017). Optimal control strategy based on neural model of nonlinear systems and evolutionary algorithms for renewable energy production as applied to biofuel generation. Journal of Renewable and Sustainable Energy, 9(3), 033101.
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- Barocio, E., Regalado, J., Cuevas, E., Uribe, F., Zúñiga, P., & Torres, P. J. R. (2017). Modified bio-inspired optimisation algorithm with a centroid decision making approach for solving a multi-objective optimal power flow problem. IET Generation, Transmission & Distribution, 11(4), 1012-1022.
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- Cuevas, E., Gálvez, J., & Avalos, O. (2017). Parameter estimation for chaotic fractional systems by using the locust search algorithm. Computación y Sistemas, 21(2), 369-380.
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- Gálvez, J., Cuevas, E., & Avalos, O. (2017). Flower pollination algorithm for multimodal optimization. International Journal of Computational Intelligence Systems, 10(1), 627-646.
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- Valdivia-Gonzalez, A., Zaldívar, D., Fausto, F., Camarena, O., Cuevas, E., & Perez-Cisneros, M. (2017). A states of matter search-based approach for solving the problem of intelligent power allocation in plug-in hybrid electric vehicles. Energies, 10(1), 92.
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- Avalos, O., Cuevas, E., & Gálvez, J. (2016). Induction motor parameter identification using a gravitational search algorithm. Computers, 5(2), 6
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- Cuevas, E., Santuario, E., Zaldivar, D., & Perez-Cisneros, M. (2016). An improved evolutionary algorithm for reducing the number of function evaluations. Intelligent Automation & Soft Computing, 22(2), 177-192.
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- Cuevas, E., Zaldívar, D., Pajares, G., Perez-Cisneros, M., & Rojas, R. (2016). Computational Intelligence in Image Processing 2016. Mathematical Problems in Engineering, 2016.
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- Osuna-Enciso, V., Cuevas, E., Oliva, D., Sossa, H., & Cisneros, M. A. P. (2016). A bio-inspired evolutionary algorithm: allostatic optimisation. IJBIC, 8(3), 154-169.
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- Osuna-Enciso, V., Zúñiga, V., Oliva, D., Cuevas, E., & Sossa, H. (2016). Image segmentation using an evolutionary method based on Allostatic mechanisms. In Image feature detectors and descriptors (pp. 255-279). Springer, Cham.
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- Osuna-Enciso, V., Cuevas, E., Oliva, D., Zúñiga, V., Pérez-Cisneros, M., & Zaldívar, D. (2016). A multiobjective approach to homography estimation. Computational intelligence and neuroscience, 2016.
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- Oliva, D., Osuna-Enciso, V., Cuevas, E., Pajares, G., Pérez-Cisneros, M., & Zaldívar, D. (2015). Improving segmentation velocity using an evolutionary method. Expert Systems with Applications, 42(14), 5874-5886.
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- Cuevas, E., & Díaz, M. (2015). A method for estimating view transformations from image correspondences based on the harmony search algorithm. Computational intelligence and neuroscience, 2015.
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- Cuevas, E., Díaz, M., & Rojas, R. (2015). Leukocyte Detection Through an Evolutionary Method. In Complex System Modelling and Control Through Intelligent Soft Computations (pp. 139-163). Springer, Cham.
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- Cuevas, E., Osuna-Enciso, V., & Oliva, D. (2015). Circle detection on images based on the Clonal Selection Algorithm (CSA). The Imaging Science Journal, 63(1), 34-44.
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- Cuevas, E., González, A., Zaldívar, D., & Pérez-Cisneros, M. (2015). An optimisation algorithm based on the behaviour of locust swarms. International Journal of Bio-Inspired Computation, 7(6), 402-407.
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- Cuevas, E., Zaldívar, D., Pajares, G., Perez-Cisneros, M., & Rojas, R. (2013). Computational intelligence in image processing. Mathematical Problems in Engineering, 2013.
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- Cuevas, E., González, A., Fausto, F., Zaldívar, D., & Pérez-Cisneros, M. (2015). Multithreshold segmentation by using an algorithm based on the behavior of locust swarms. Mathematical Problems in Engineering, 2015.
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- Perez-Cisneros, M., Garcia-Gil, G., Vega-Maldonado, S., Arámburo-Lizárraga, J., Cuevas, E., & Zaldivar, D. (2015). Applying BAT evolutionary optimization to image-based visual servoing. Mathematical Problems in Engineering, 2015.
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- Cuevas, E., Cienfuegos, M., Rojas, R., & Padilla, A. (2015). A computational intelligence optimization algorithm based on the behavior of the social-spider. In Computational Intelligence Applications in Modeling and Control (pp. 123-146). Springer, Cham.
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- Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Osuna, V. (2014). A multilevel thresholding algorithm using electromagnetism optimization. Neurocomputing, 139, 357-381.
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- Oliva, D., Cuevas, E., & Pajares, G. (2014). Parameter identification of solar cells using artificial bee colony optimization. Energy, 72, 93-102.
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- Cuevas, E., González, M., Zaldivar, D., & Pérez-Cisneros, M. (2014). Multi-ellipses detection on images inspired by collective animal behavior. Neural Computing and Applications, 24(5), 1019-1033.
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- Cuevas, E., Echavarría, A., & Ramírez-Ortegón, M. A. (2014). An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation. Applied intelligence, 40(2), 256-272.
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- Cuevas, E., & Reyna-Orta, A. (2014). A cuckoo search algorithm for multimodal optimization. The Scientific World Journal, 2014.
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- Cuevas, E., & Cienfuegos, M. (2014). A new algorithm inspired in the behavior of the social-spider for constrained optimization. Expert Systems with Applications, 41(2), 412-425.
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- Oliva, D., Cuevas, E., Pajares, G., & Zaldivar, D. (2014). Template matching using an improved electromagnetism-like algorithm. Applied intelligence, 41(3), 791-807.
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- Cuevas, E., Gálvez, J., Hinojosa, S., Avalos, O., Zaldívar, D., & Pérez-Cisneros, M. (2014). A comparison of evolutionary computation techniques for IIR model identification. Journal of Applied Mathematics, 2014.
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- Ramírez-Ortegón, M. A., Ramírez-Ramírez, L. L., Messaoud, I. B., Märgner, V., Cuevas, E., & Rojas, R. (2014). A model for the gray-intensity distribution of historical handwritten documents and its application for binarization. International Journal on Document Analysis and Recognition (IJDAR), 17(2), 139-160.
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- Ramírez-Ortegón, M. A., Ramírez-Ramírez, L. L., Märgner, V., Messaoud, I. B., Cuevas, E., & Rojas, R. (2014). An analysis of the transition proportion for binarization in handwritten historical documents. Pattern recognition, 47(8), 2635-2651.
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- Cuevas, E., Santuario, E. L., Zaldívar, D., & Perez-Cisneros, M. (2013). Automatic circle detection on images based on an evolutionary algorithm that reduces the number of function evaluations. Mathematical Problems in Engineering, 2013.
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- Cuevas, E., & Ortega-Sánchez, N. (2014). Harmony Search Algorithm and its Use in Digital Image Processing. Computación y Sistemas, 17(4), 543-560.
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- Cuevas, E., Zaldívar, D., Pajares, G., Perez-Cisneros, M., & Rojas, R. (2013). Computational intelligence in image processing. Mathematical Problems in Engineering, 2013.
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- Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Perez-Cisneros, M. (2013). Multilevel thresholding segmentation based on harmony search optimization. Journal of Applied Mathematics, 2013.
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- Cuevas, E., Sención-Echauri, F., Zaldivar, D., & Pérez, M. (2013). Image segmentation using artificial Bee colony optimization. In Handbook of Optimization (pp. 965-990). Springer, Berlin, Heidelberg.
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- Cuevas, E., Oliva, D., Zaldivar, D., Pérez, M., & Rojas, R. (2013). Circle detection algorithm based on electromagnetism-like optimization. In Handbook of Optimization (pp. 907-934). Springer, Berlin, Heidelberg.
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- Cuevas, E., EchavarríA, A., ZaldíVar, D., & PéRez-Cisneros, M. (2013). A novel evolutionary algorithm inspired by the states of matter for template matching. Expert Systems with Applications, 40(16), 6359-6373.
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- Cuevas, E., Cienfuegos, M., ZaldíVar, D., & Pérez-Cisneros, M. (2013). A swarm optimization algorithm inspired in the behavior of the social-spider. Expert Systems with Applications, 40(16), 6374-6384.
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- Cuevas, E. (2013). Block-matching algorithm based on harmony search optimization for motion estimation. Applied intelligence, 39(1), 165-183.
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- Cuevas, E., & González, M. (2013). Multi-circle detection on images inspired by collective animal behavior. Applied intelligence, 39(1), 101-120.
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- Cuevas, E., Díaz, M., Manzanares, M., Zaldivar, D., & Perez-Cisneros, M. (2013). An improved computer vision method for white blood cells detection. Computational and mathematical methods in medicine, 2013.
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- Ramírez-Ortegón, M. A., Märgner, V., Cuevas, E., & Rojas, R. (2013). An optimization for binarization methods by removing binary artifacts. Pattern Recognition Letters, 34(11), 1299-1306.
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- Cuevas, E., Zaldívar, D., & Pérez-Cisneros, M. (2013). A swarm optimization algorithm for multimodal functions and its application in multicircle detection. Mathematical Problems in Engineering, 2013.
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- Zaldivar, D., Cuevas, E., Pérez-Cisneros, M. A., Sossa, J. H., Rodríguez, J. G., & Palafox, E. O. (2013). An educational fuzzy-based control platform using LEGO robots. International Journal of Electrical Engineering Education, 50(2), 157-171.
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- Cuevas, E., Oliva, D., Díaz, M., Zaldivar, D., Pérez-Cisneros, M., & Pajares, G. (2013). White blood cell segmentation by circle detection using electromagnetism-like optimization. Computational and mathematical methods in medicine, 2013.
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- Cuevas, E., & Sossa, H. (2013). A comparison of nature inspired algorithms for multi-threshold image segmentation. Expert Systems with Applications, 40(4), 1213-1219.
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- Cuevas, E., & González, M. (2013). An optimization algorithm for multimodal functions inspired by collective animal behavior. Soft Computing, 17(3), 489-502.
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- Osuna, V., Cuevas, E., & Sossa, H. (2013). Segmentation of blood cell images using evolutionary methods. In EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (pp. 299-311). Springer, Berlin, Heidelberg.
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- Cuevas, E., ZaldíVar, D., Pérez-Cisneros, M., & Oliva, D. (2013). Block-matching algorithm based on differential evolution for motion estimation. Engineering Applications of Artificial Intelligence, 26(1), 488-498.
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- Cuevas, E., Wario, F., Zaldivar, D., & Pérez-Cisneros, M. (2012). Circle detection on images using learning automata. IET computer vision, 6(2), 121-132.
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- Cuevas, E., Zaldívar, D., Pérez-Cisneros, M., Sossa, H., & Osuna, V. (2013). Block matching algorithm for motion estimation based on Artificial Bee Colony (ABC). Applied Soft Computing, 13(6), 3047-3059.
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- Cuevas, E., Sossa, H., Osuna, V., Zaldivar, D., & Pérez-Cisneros, M. (2013). Fast circle detection using harmony search optimization. In EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II (pp. 313-325). Springer, Berlin, Heidelberg.
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- Cuevas, E., Oliva, D., Zaldivar, D., Perez, M., & Pajares, G. (2014). Opposition Based ElectromagnetismLike for Global Optimization. arXiv preprint arXiv:1405.5172.
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- Cuevas, E., Wario, F., Osuna-Enciso, V., Zaldivar, D., & Pérez-Cisneros, M. (2012). Fast algorithm for multiple-circle detection on images using learning automata. IET Image Processing, 6(8), 1124-1135.
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- Cuevas, E., Sención, F., Zaldivar, D., Pérez-Cisneros, M., & Sossa, H. (2012). A multi-threshold segmentation approach based on artificial bee colony optimization. Applied Intelligence, 37(3), 321-336.
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- Cuevas, E., Osuna-Enciso, V., Zaldivar, D., Perez-Cisneros, M., & Sossa, H. (2012). Multithreshold segmentation based on artificial immune systems. Mathematical Problems in Engineering, 2012.
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- Cuevas, E., Ortega-Sánchez, N., Zaldivar, D., & Pérez-Cisneros, M. (2012). Circle detection by harmony search optimization. Journal of Intelligent & Robotic Systems, 66(3), 359-376.
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- Cuevas, E., Gonzalez, M., Zaldivar, D., Perez-Cisneros, M., & García, G. (2012). An algorithm for global optimization inspired by collective animal behavior. Discrete Dynamics in Nature and Society, 2012.
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- Cuevas, E., Wario, F., Zaldivar, D., & Pérez-Cisneros, M. (2012). Circle detection on images using learning automata. IET computer vision, 6(2), 121-132.
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- Cuevas, E., Sención-Echauri, F., Zaldivar, D., & Pérez-Cisneros, M. (2012). Multi-circle detection on images using artificial bee colony (ABC) optimization. Soft Computing, 16(2), 281-296.
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- Cuevas, E., Osuna-Enciso, V., Wario, F., Zaldívar, D., & Pérez-Cisneros, M. (2012). Automatic multiple circle detection based on artificial immune systems. Expert Systems with Applications, 39(1), 713-722.
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- Cuevas, E., Oliva, D., Zaldivar, D., Pérez-Cisneros, M., & Sossa, H. (2012). Circle detection using electro-magnetism optimization. Information Sciences, 182(1), 40-55.
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- Sossa-Azuela, J. H., Cuevas-Jiménez, E. B., & Zaldivar-Navarro, D. (2011). Alternative way to compute the Euler Number of a binary image. Journal of applied research and technology, 9(3), 335-341.
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- Cuevas, E., Zaldivar, D., Perez-Cisneros, M., & Rojas, R. (2011). Learning Automata in Control Planning Strategies. In Intelligent Computational Optimization in Engineering (pp. 27-54). Springer, Berlin, Heidelberg.
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- Cuevas, E., Zaldivar, D., & Pérez-Cisneros, M. (2011). Seeking multi-thresholds for image segmentation with Learning Automata. Machine Vision and Applications, 22(5), 805-818.
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- Ramírez-Ortegón, M. A., Duéñez-Guzmán, E. A., Rojas, R., & Cuevas, E. (2011). Unsupervised measures for parameter selection of binarization algorithms. Pattern Recognition, 44(3), 491-502.
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- Cuevas, E., Zaldivar, D., Pérez-Cisneros, M., & Ramirez-Ortegon, M. (2011). Hands-on experiments on intelligent behaviour for mobile robots. International Journal of Electrical Engineering Education, 48(1), 66-78.
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- Cuevas, E., Zaldivar, D., Pérez-Cisneros, M., & Ramírez-Ortegón, M. (2011). Circle detection using discrete differential evolution optimization. Pattern Analysis and Applications, 14(1), 93-107.
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- Cuevas, E., Zaldivar, D., Pérez-Cisneros, M., Sánchez, E., & Ramírez-Ortegón, M. (2011). Robust Fuzzy Corner Detector. Intelligent Automation & Soft Computing, 17(4), 415-429.
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- Sossa-Azuela, J. H., Cuevas-Jiménez, E. V., & Zaldivar-Navarro, D. (2010). Computation of the Euler number of a binary image composed of hexagonal cells. Journal of applied research and technology, 8(3), 340-350.
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- Cuevas, E., Zaldivar, D., Perez, M., & Ramirez, M. (2014). Polynomial trajectory algorithm for a biped robot. arXiv preprint arXiv:1405.5937.
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- Ramírez-Ortegón, M. A., Tapia, E., Rojas, R., & Cuevas, E. (2010). Transition thresholds and transition operators for binarization and edge detection. Pattern Recognition, 43(10), 3243-3254.
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- Cuevas, E., Zaldivar, D., & Pérez-Cisneros, M. (2010). A novel multi-threshold segmentation approach based on differential evolution optimization. Expert Systems with Applications, 37(7), 5265-5271.
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- Cuevas, E., Zaldivar, D., & Pérez-Cisneros, M. (2010). Low-cost commercial Lego™ platform for mobile robotics. International Journal of Electrical Engineering Education, 47(2), 132-150.
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- Ramírez-Ortegón, M. A., Tapia, E., Ramírez-Ramírez, L. L., Rojas, R., & Cuevas, E. (2010). Transition pixel: A concept for binarization based on edge detection and gray-intensity histograms. Pattern Recognition, 43(4), 1233-1243.
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- Cuevas, E., Zaldivar, D., & Rojas, R. (2009). Neurofuzzy prediction for gaze control. Canadian Journal of Electrical and Computer Engineering, 34(1/2), 15-20.
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- Cuevas, E., Zaldivar, D., Perez, M., & Sanchez, E. N. (2009). LVQ neural networks applied to face segmentation. Intelligent Automation & Soft Computing, 15(3), 439-450.
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