Artículos científicos JCR

1. Aguirre, N., Cuevas, E., Luque-Chang, A., Barba-Toscano, O., & Vasquez-Franco, M. (2026). Covariance Matrix Adaptation Evolution Strategy (CMA-ES): A Comprehensive Survey of Variants and Hybridizations. Archives of Computational Methods in Engineering, 1-57.

2. González, A., Gutiérrez, V. G., Cuevas, E., & Pérez-Cisneros, M. (2026). A two-stage preprocessing and classification approach for accurate COVID-19 detection in X-ray images. Scientific Reports.

3. Barba-Toscano, O., Cuevas, E., Escobar-Cuevas, H., Vásquez, M., & Aguirre, N. (2026). Application of the golden section and the Latin hypercube sampling on metaheuristics: A new population initialization approach. Evolutionary Intelligence, 19(2), 32.

4. Gayen, S., Maity, S., Sarkar, S., Cuevas, E., & Sarkar, R. (2026). SEFFNet: snapshot ensemble-based feature fusion network for skin cancer classification. International Journal of Machine Learning and Cybernetics, 17(3), 139.

5. Cuevas, E., González, O., Escobar, H., Ayala, L., Zaldívar, D., Pérez-Cisneros, M., & Rodríguez, A. (2026). Overcoming Center-Bias behavior: A Metaheuristic Algorithm with Dual Operators for Optimized Search and Refinement. Systems and Soft Computing, 200436.

6. Ali, A., Pal, R., Dey, I., Cuevas, E., Perez-Cisneros, M., & Sarkar, R. (2025). DANet a lightweight dilated attention network for malaria parasite detection. Scientific Reports, 15(1), 36689.

7. Roy, A., Pani, S., Malakar, S., Cuevas, E., Pérez-Cisneros, M., & Sarkar, R. (2025). JUHCCR-v1: a database for hand-drawn electrical and electronics circuit component recognition. Scientific Reports, 15(1), 38617.

8. Cuevas, E., González, O., Orozco-Jiménez, F., Zaldívar, D., Rodríguez-Vazquez, A., & Sarkar, R. (2025). Expansion-Trajectory Optimization (ETO): A dual-operator metaheuristic for balanced global and local search. Applied Soft Computing, 113642.

9. Toski, M., Cuevas, E., Escobar, H., Morales-Castañeda, B., & Pérez-Cisneros, M. (2025). Simulating flood situations in urban hydrology using a diffusion model in complex networks. Stochastic Environmental Research and Risk Assessment, 39(10), 4891-4909.

10. Cuevas, E., González-Sánchez, Ó. A., Gómez-Gracián, I., Zaldívar, D., Rodríguez-Vázquez, A. N., & Sarkar, R. (2025). Bezier-based exploration and hexagonal crossover exploitation: a novel metaheuristic approach. Evolutionary Intelligence, 18(4), 83.

11. Cuevas, E., González-Sánchez, Ó. A., Escobar, H., Ayala, L. E., & Zaldívar, D. (2025). Filling space swarm optimization (FSSO): a metaheuristic algorithm with divided agent strategies and diamond crossover. The Journal of Supercomputing, 81(11), 1172.

12. Barba-Toscano, O., Cuevas, E., Escobar-Cuevas, H., & Islas-Toski, M. (2025). Cellular neighbors optimizer: a novel metaheuristic approach inspired by the cellular automata and agent-based modeling for global optimization. The Journal of Supercomputing, 81(8), 1-50.

13. Morales-Castañeda, B., Pérez-Cisneros, M., Cuevas, E., Zaldívar, D., Toski, M., & Rodríguez, A. (2025). Analyzing metaheuristic algorithms performance and the causes of the zero-bias problem: a different perspective in benchmarks. Evolutionary Intelligence, 18(2), 1-19.

14. Cuevas, E., González-Sánchez, O. A., Delgado-Castañeda, N., Zaldívar, D., & Rodríguez-Vazquez, A. (2025). A novel metaheuristic algorithm using structured population and virtual particles. The Journal of Supercomputing, 81(6), 1-90.

15. Aguirre, N., Cuevas, E., Luque-Chang, A., & Escobar-Cuevas, H. (2025). An improved swarm optimization algorithm using exploration and evolutionary game theory for efficient exploitation. The Journal of Supercomputing, 81(4), 1-57.

16. Cuevas, E., Barba, O., & Escobar, H. (2025). A novel cheetah optimizer hybrid approach based on opposition-based learning (OBL) and diversity metrics. Computing, 107(2), 62.

17. Escobar-Cuevas, H., Cuevas, E., Lopez, J., & Perez-Cisneros, M. (2025). Integration of metaheuristic operators through unstructured evolutive game theory approach: a novel hybrid methodology. Evolutionary Intelligence, 18(1), 1-28.

18.Cuevas, E., García-De-Lira, S. J., Ascencio-Piña, C. R., Pérez-Cisneros, M., & Vega, S. (2025). Integrating agent-based models and clustering methods for improving image segmentation. Heliyon, 11(1).

19. Cuevas, E. H., Zaldivar, D., & Perez, M. (2025). Impact of Programming Languages on Learning Performance. International Journal of Information and Communication Technology Education (IJICTE), 21(1), 1-17.

20. Islas-Toski, M., Cuevas, E., Pérez-Cisneros, M., & Escobar, H. (2024). Agent-Based Evacuation Modeling: Enhancing Building Safety in Emergency Scenarios. Smart Cities, 7(6), 3165-3187.

21. Escobar-Cuevas, H., Cuevas, E., Luque-Chang, A., Barba-Toscano, O., & Pérez-Cisneros, M. (2024). Enhancing Metaheuristic Algorithm Performance Through Structured Population and Evolutionary Game Theory. Mathematics, 12(23), 3676.

22. Rivera-Aguilar, B. A., Cuevas, E., Luque-Chang, A., López, J., & Pérez-Cisneros, M. (2024). Pixel Interaction Model for Contrast Enhancement: Bridging Social Science and Image Processing. Applied Sciences, 14(23), 10887.

23. Rivera-Aguilar, B. A., Cuevas, E., Zaldívar, D., & Pérez-Cisneros, M. A. (2024). A metaheuristic algorithm based on a radial basis function neural networks. Neural Computing and Applications, 1-29.

24. Cuevas, E., Vásquez, M., Avila, K., Rodriguez, A., & Zaldivar, D. (2025). Balancing individual and collective strategies: A new approach in metaheuristic optimization. Mathematics and Computers in Simulation, 227, 322-346.

25. Cuevas, E., Ascencio-Piña, C. R., Pérez, M., & Morales-Castañeda, B. (2024). Considering radial basis function neural network for effective solution generation in metaheuristic algorithms. Scientific Reports, 14(1), 16806.

26. Cuevas, E., Barba-Toscano, O., Escobar, H., Zaldívar, D., & Rodríguez-Vázquez, A. (2024). An initialization approach for metaheuristic algorithms by using Gibbs sampling. Mathematics and Computers in Simulation, 225, 586-606.

27. Toski, M., Cuevas, E., Avila, K., & Perez-Cisneros, M. (2024). Enhancing Bicycle Trajectory Planning in Urban Environments through Complex Network Optimization. Journal of Urban Planning and Development, 150(3), 04024023.

28. García-Gutiérrez, V., González, A., Cuevas, E., Fausto, F., & Pérez-Cisneros, M. (2024). Detection of COVID-19: A Metaheuristic-Optimized Maximally Stable Extremal Regions Approach. Symmetry, 16(7), 870.

29. Cuevas, E., Luque, A., Aguirre, N., Navarro, M. A., & Rodríguez, A. (2024). Metaheuristic optimization with dynamic strategy adaptation: An evolutionary game theory approach. Physica A: Statistical Mechanics and its Applications, 645, 129831.

30. Rivera-Aguilar, B. A., Cuevas, E., Pérez, M., Camarena, O., & Rodríguez, A. (2024). A new histogram equalization technique for contrast enhancement of grayscale images using the differential evolution algorithm. Neural Computing and Applications, 1-17.

31. Escobar-Cuevas, H., Cuevas, E., Avila, K., & Avalos, O. (2024). An advanced initialization technique for metaheuristic optimization: a fusion of Latin hypercube sampling and evolutionary behaviors. Computational and Applied Mathematics, 43(4), 234.

32. Ascencio-Piña, C., García-De-Lira, S., Cuevas, E., & Pérez, M. (2024). Image segmentation with Cellular Automata. Heliyon, 10(10).

33. Pramanik, P., Roy, A., Cuevas, E., Perez-Cisneros, M., & Sarkar, R. (2024). DAU-Net: Dual attention-aided U-Net for segmenting tumor in breast ultrasound images. Plos one, 19(5), e0303670.

34. Escobar-Cuevas, H., Cuevas, E., Gálvez, J., & Toski, M. (2024). A novel optimization approach based on unstructured evolutionary game theory. Mathematics and Computers in Simulation, 219, 454-472.

35. Eid, H. F., Cuevas, E., & Mansour, R. F. (2024). Autonomous bonobo optimization algorithm for power allocation in wireless networks. Mathematics and Computers in Simulation, 217, 294-310.

36. Naskar, G., Mohiuddin, S., Malakar, S., Cuevas, E., & Sarkar, R. (2024). Deepfake detection using deep feature stacking and meta-learning. Heliyon, 10(4).

37. Escobar-Cuevas, H., Cuevas, E., Gálvez, J., & Avila, K. (2024). A novel hybrid search strategy for evolutionary fuzzy optimization approach. Neural Computing and Applications, 36(6), 2633-2652.

38. Eid, H., & Cuevas, E. (2024). Enhanced bonobo optimizer for optimizing dynamic photovoltaic models. Computer Science, 25(3).

39. Cuevas, E., Luque, A., Vega, F., Zaldívar, D., & López, J. (2024). Social influence dynamics for image segmentation: a novel pixel interaction approach. Journal of Computational Social Science, 1-30.

40. Cuevas, E., Guzmán-Rosales, C., Perez, M., & Sarkar, R. (2024). A graph segmentation method based on compatibility subgraph aggregation. IEEE Access.

41. González-Sánchez, Ó. A., Zaldívar, D., Cuevas, E., & González-Ortiz, L. J. (2024). Mathematical Optimization Strategy for Effectiveness Profile Estimation in Two-Dose Vaccines and Its Use in Designing Improved Vaccination Strategies Focused on Pandemic Containment. Vaccines, 12(1), 81.

42. Zarate, O., Zaldívar, D., Cuevas, E., & Perez, M. (2023). Enhancing pneumonia segmentation in lung radiographs: a jellyfish search optimizer approach. Mathematics, 11(20), 4363.

43. Cuevas, E., Rodríguez, A., Perez, M., Murillo-Olmos, J., Morales-Castañeda, B., Alejo-Reyes, A., & Sarkar, R. (2023). Optimal evaluation of re-opening policies for COVID-19 through the use of metaheuristic schemes. Applied Mathematical Modelling, 121, 506-523.

44. Mukhopadhyay, S., Hossain, S., Malakar, S., Cuevas, E., & Sarkar, R. (2023). Image contrast improvement through a metaheuristic scheme. Soft Computing, 27(18), 13657-13676.

45. Cuevas, E., Escobar, H., Sarkar, R., & Eid, H. F. (2023). A new population initialization approach based on Metropolis–Hastings (MH) method. Applied Intelligence, 53(13), 16575-16593.

46. Alejo-Reyes, A., Mendoza, A., Cuevas, E., & Alcaraz-Rivera, M. (2023). A Mathematical Model for an Inventory Management and Order Quantity Allocation Problem with Nonlinear Quantity Discounts and Nonlinear Price-Dependent Demand. Axioms, 12(6), 547.

47. Gonzalez-Ayala, P., Alejo-Reyes, A., Cuevas, E., & Mendoza, A. (2023). A modified simulated annealing (MSA) algorithm to solve the supplier selection and order quantity allocation problem with non-linear freight rates. Axioms, 12(5), 459.

48. Corona, G., Maciel-Castillo, O., Morales-Castañeda, J., Gonzalez, A., & Cuevas, E. (2023). A new method to solve rotated template matching using metaheuristic algorithms and the structural similarity index. Mathematics and Computers in Simulation, 206, 130-146.

49. Haro, E. H., Avalos, O., Camarena, O., & Cuevas, E. (2023). An accurate flexible process planning using an adaptive genetic algorithm. Neural Computing and Applications, 35(9), 6435-6456.

50. Avila, K., Cuevas, E., Perez, M., & Sarkar, R. (2023). A new metaphor-free metaheuristic approach based on complex networks and Bezier curves. IEEE Access.

51. Escobar, H., Cuevas, E., Toski, M. I., Ramirez, F. J. C., & Pérez-Cisneros, M. (2023). An Agent-Based Model for Public Security Strategies by Predicting Crime Patterns. IEEE Access, 11, 67070-67085.

52. Chavarín, Á., Cuevas, E., Avalos, O., Gálvez, J., & Pérez-Cisneros, M. (2023). Contrast enhancement in images by homomorphic filtering and cluster-chaotic optimization. IEEE Access, 11, 73803-73822.

53. Ayala, E., Cuevas, E., Zaldívar, D., & Pérez, M. (2023). Image segmentation by agent-based pixel homogenization. IEEE Access, 11, 54221-54239.

54. Gálvez, J., Cuevas, E., Michel, D. E. B., Rodríguez, A., & Pérez-Cisneros, M. A. (2023). Multi-Circle Detection Guided by Multimodal Optimization Scheme. IEEE Access, 11, 47884-47906.

55. Luque-Chang, A., Cuevas, E., Chavarin, A., & Perez, M. (2023). Agent-based image contrast enhancement algorithm. IEEE Access, 11, 6060-6077.

56. Banerjee, D., Bhowal, P., Malakar, S., Cuevas, E., Pérez‑Cisneros, M., & Sarkar, R. (2022). Z-transform-based profile matching to develop a learning-free keyword spotting method for handwritten document images. International Journal of Computational Intelligence Systems, 15(1), 93.

57. Eid, H. F., Mansour, R. F., & Cuevas, E. (2022). A modified variant of coyote optimization algorithm for solving ordinary differential equations and oscillatory mechanical problems. Simulation, 98(12), 1161-1178.

58. Chattopadhyay, S., Dey, A., Singh, P. K., Oliva, D., Cuevas, E., & Sarkar, R. (2022). MTRRE-Net: A deep learning model for detection of breast cancer from histopathological images. Computers in Biology and Medicine, 150, 106155.

59. Ganguly, S., Mohiuddin, S., Malakar, S., Cuevas, E., & Sarkar, R. (2022). Visual attention-based deepfake video forgery detection. Pattern Analysis and Applications, 25(4), 981-992.

60. Rodríguez, A., Cuevas, E., Zaldivar, D., Morales-Castañeda, B., Sarkar, R., & Houssein, E. H. (2022). An agent-based transmission model of COVID-19 for re-opening policy design. Computers in Biology and Medicine, 148, 105847.

61. Kundu, R., Chattopadhyay, S., Cuevas, E., & Sarkar, R. (2022). AltWOA: Altruistic Whale Optimization Algorithm for feature selection on microarray datasets. Computers in biology and medicine, 144, 105349.

62. Basu, A., Sheikh, K. H., Cuevas, E., & Sarkar, R. (2022). COVID-19 detection from CT scans using a two-stage framework. Expert Systems with Applications, 193, 116377.

63. Cuevas, E., Zaldivar, D., & Perez, M. (2022). Metaheuristic schemes and machine learning techniques: A synergistic perspective. Applied Mathematical Modelling, 104, 850-851.

64. Rafe, V., Mohammady, S., & Cuevas, E. (2022). Using Bayesian optimization algorithm for model-based integration testing. Soft Computing, 26(7), 3503-3525.

65. Osuna-Enciso, V., Cuevas, E., & Castañeda, B. M. (2022). A diversity metric for population-based metaheuristic algorithms. Information Sciences, 586, 192-208.

66. Guha, R., Ghosh, S., Ghosh, K. K., Cuevas, E., Perez-Cisneros, M., & Sarkar, R. (2022). Groundwater flow algorithm: A novel hydro-geology based optimization algorithm. IEEE Access, 10, 132193-132211.

67. Xu, Q., Rocha, A. M. A., Cuevas, E., & Fister Jr, I. (2022). Nature-Inspired Intelligence Methods and Applications. Mathematical Problems in Engineering, 2022.

68. Chakraborty, A., Ghosh, K. K., De, R., Cuevas, E., & Sarkar, R. (2021). Learning automata based particle swarm optimization for solving class imbalance problem. Applied Soft Computing, 113, 107959.

69. Cuevas, E., Gálvez, J., Toski, M., & Avila, K. (2021). Evolutionary-Mean shift algorithm for dynamic multimodal function optimization. Applied Soft Computing, 113, 107880.

70. Rosas-Caro, J. C., García-Vite, P. M., Rodríguez, A., Mendoza, A., Alejo-Reyes, A., Cuevas, E., & Beltran-Carbajal, F. (2021). Differential evolution based algorithm for optimal current ripple cancelation in an unequal interleaved power converter. Mathematics, 9(21), 2755.

71. Bandyopadhyay, R., Basu, A., Cuevas, E., & Sarkar, R. (2021). Harris Hawks optimisation with Simulated Annealing as a deep feature selection method for screening of COVID-19 CT-scans. Applied Soft Computing, 111, 107698.

72. Houssein, E. H., Hussain, K., Abualigah, L., Abd Elaziz, M., Alomoush, W., Dhiman, G., ... & Cuevas, E. (2021). An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation. Knowledge-based systems, 229, 107348.

73. 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.

74. Rodríguez, A., Pérez-Cisneros, M., Rosas-Caro, J. C., Del-Valle-Soto, C., Gálvez, J., & Cuevas, E. (2021). Robust clustering routing method for wireless sensor networks considering the Locust search scheme. Energies, 14(11), 3019.

75. Rodríguez, A., Camarena, O., Cuevas, E., Aranguren, I., Valdivia-G, A., Morales-Castañeda, B., ... & Pérez-Cisneros, M. (2021). Group-based synchronous-asynchronous grey wolf optimizer. Applied Mathematical Modelling, 93, 226-243.

76. 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.

77. Zaldivar, D., Cuevas, E., Maciel, O., Valdivia, A., Chavolla, E., & Oliva, D. (2021). 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.

78. Cuevas, E., Gálvez, J., Avalos, O., & Chavarin, Á. (2021). A mean shift segmentation scheme using several pixel characteristics. Computers & Electrical Engineering, 90, 107022.

79. 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, 12435-12468.

80. Cuevas, E., Becerra, H., & Luque, A. (2021). Anisotropic diffusion filtering through multi-objective optimization. Mathematics and Computers in Simulation, 181, 410-429.

81. 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.

82. Cuevas, E., Becerra, H., Luque, A., & Abd Elaziz, M. (2021). Fast multi-feature image segmentation. Applied Mathematical Modelling, 90, 742-757.

83. 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.

84. 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, 48(16-17), 1708-1721.

85. del Río, A. H., Aranguren, I., Oliva, D., Elaziz, M. A., & Cuevas, E. (2021). Efficient image segmentation through 2D histograms and an improved owl search algorithm. International Journal of Machine Learning and Cybernetics, 12, 131-150.

86. 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.

87. 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.

88. 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.

89. 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.

90. Rodriguez, A., Cuevas, E., Zaldivar, 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.

91. 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.

92. 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.

93. Gálvez, J., Cuevas, E., & Gopal Dhal, K. (2020). A competitive memory paradigm for multimodal optimization driven by clustering and chaos. Mathematics, 8(6), 934.

94. Cuevas, E. (2020). An agent-based model to evaluate the COVID-19 transmission risks in facilities. Computers in biology and medicine, 121, 103827.

95. Morales-Castañeda, B., Zaldivar, D., Cuevas, E., Fausto, F., & Rodríguez, A. (2020). A better balance in metaheuristic algorithms: Does it exist?. Swarm and Evolutionary Computation, 54, 100671.

96. Cuevas, E., Oliva, D., & Osuna, V. (2020). Bio-inspired algorithms and Bio-systems. Mathematical Biosciences and Engineering, 17(3), 2400-2402.

97. 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), 1059-1071.

98. Maciel, O., Valdivia, A., Oliva, D., Cuevas, E., Zaldivar, D., & Pérez-Cisneros, M. (2020). A novel hybrid metaheuristic optimization method: hypercube natural aggregation algorithm. Soft Computing, 24, 8823-8856.

99. Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Pérez-Cisneros, M. (2020). Reducing overlapped pixels: a multi-objective color thresholding approach. Soft Computing, 24, 6787-6807.

100. Zaldivar, D., Cuevas, E., Maciel, O., Valdivia, A., Chavolla, E., & Oliva, D. (2021). 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.

101. Maciel C., O., Cuevas, E., Navarro, M.A., Zaldívar, D., Hinojosa, S., Side-Blotched Lizard Algorithm: A polymorphic population approach, Applied Soft Computing Journal, 88,(2020), 106039.

102. Gálvez, J., Cuevas, E., Becerra, H., Avalos, O., A hybrid optimization approach based on clustering and chaotic sequences, International Journal of Machine Learning and Cybernetics, 11(2), (2020), 359-401.

103. Fausto, F., Reyna-Orta, A., Cuevas, E., Andrade, Á.G., Perez-Cisneros, M., From ants to whales: metaheuristics for all tastes, Artificial Intelligence Review, 53(1), (2020), 753-810.

104. Ibrahim, R.A., Elaziz, M.A., Oliva, D., Cuevas, E., Lu, S., An opposition-based social spider optimization for feature selection, Soft Computing, 23(24), (2019), 13547-13567.

105. Cuevas, E., Rodríguez, A., Valdivia, A., Zaldívar, D., Pérez, M., A hybrid evolutionary approach based on the invasive weed optimization and estimation distribution algorithms, Soft Computing, 23(24), (2019), 13627-13668.

106. Cuevas, E., Galvez, J. An optimization algorithm guided by a machine learning approach, International Journal of Machine Learning and Cybernetics, 10(11), (2019), 2963-2991.

107. Morales-Castañeda, B., Zaldívar, D., Cuevas, E., Aranguren, I., Fausto, F., An improved Simulated Annealing algorithm based on ancient metallurgy techniques, Applied Soft Computing Journal, 84, (2019), 105761.

108. Rodríguez, A., Cuevas, E., Zaldivar, D., Castañeda, L., Clustering with biological visual models, Physica A: Statistical Mechanics and its Applications, 528, (2019), 121505.

109. Cuevas, E., Díaz-Cortes, M.-A., Mezura-Montes, E., Corner detection of intensity images with cellular neural networks (CNN) and evolutionary techniques, Neurocomputing, 347, (2019), 82-93.

110. Fausto, F., Cuevas, E., Maciel-Castillo, O., Morales-Castañeda, B., 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), (2019), 676-696.

111. Avalos, O., Cuevas, E., Valdivia-González, A., Zaldívar, D., Oliva, D., A comparative study of evolutionary computation techniques for solar cells parameter estimation, Computacion y Sistemas, 23(1), (2019), 231-256.

112. Díaz Primitivo, Rodríguez Alma, Cuevas Erik, Valdivia Arturo, Zaldívar Daniel, A hybrid method for blood vessel segmentation in images, Biocybernetics and Biomedical Engineering, 39(3), (2019), 814-824.

113. Jorge Gálvez, Erik Cuevas, Salvador Hinojosa, Omar Avalos, Marco Pérez-Cisneros, A reactive model based on neighborhood consensus for continuous optimization, Expert Systems with Applications, 121, (2019), 115-141.

114. Cuevas, E., Díaz, P., Avalos, O., Zaldívar, D., Pérez-Cisneros, M., Nonlinear system identification based on ANFIS-Hammerstein model using Gravitational search algorithm, Applied Intelligence, 48(1), (2018), 182–203.

115. Hinojosa, S., Dhal, K.G., Elaziz, M.A., Oliva, D., Cuevas, E, Entropy-based imagery segmentation for breast histology using the Stochastic Fractal Search, Neurocomputing, 321, (2018), 201-215.

116. Zaldívar, D., Morales, B., Rodríguez, A., Valdivia-G, A., Cuevas, E., Pérez-Cisneros, M. A novel bio-inspired optimization model based on Yellow Saddle Goatfish Behavior, BioSystems, 174, (2018), 1-21.

117. Hinojosa, S., Avalos, O., Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., Gálvez, J., Unassisted thresholding based on multi-objective evolutionary algorithms, Knowledge-Based Systems, 159, (2018), 221-232.

118. Cuevas, E., Enríquez, L., Zaldívar, D., Pérez-Cisneros, M., A selection method for evolutionary algorithms based on the Golden Section, Expert Systems with Applications, 106, (2018), 183-196.

119. Díaz, P., Pérez-Cisneros, M., Cuevas, E., Camarena, O., Martinez, F.A.F., González, A., A swarm approach for improving voltage profiles and reduce power loss on electrical distribution networks, IEEE Access, (2018), 6,8457499, 49498-49512.

120. Gálvez, J., Cuevas, E., Avalos, O., Oliva, D., Hinojosa, S., Electromagnetism-like mechanism with collective animal behavior for multimodal optimization, Applied Intelligence, 48(9),(2018), 2580–2612.

121. Díaz-Cortés, M, Ortega-Sánchez, N, Hinojosa, S., Oliva, D., Cuevas, E., Rojas, R., Demin, A., A multi-level thresholding method for breast thermograms analysis using Dragonfly algorithm, Infrared Physics and Technology, 93, (2018), 346-361.

122. Cuevas, E., Reyna-Orta, A., Díaz-Cortes, M.-A., A Multimodal Optimization Algorithm Inspired by the States of Matter, Neural Processing Letters, 48(1),(2018), 517-556.

123. Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Avalos, O., Gálvez, J., Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm, Neural Computing and Applications, 29(8), (2018), 319-335.

124. Díaz, P., Pérez-Cisneros, M., Cuevas, E., Avalos, O., Gálvez, J., Hinojosa, S., Zaldivar, D., An improved crow search algorithm applied to energy problems, Energies, 11(3), (2018), 571.

125. Cuevas, E., Zaldívar, D., Pajares, G., Perez-Cisneros, M., Rojas, R., Computational Intelligence in Image Processing 2018, Mathematical Problems in Engineering, 2018, 6952803.

126. Chang, Erik Cuevas, Fernando Fausto, Daniel Zaldívar, and Marco Pérez, Social Spider Optimization Algorithm: Modifications, Applications, and Perspectives, Mathematical Problems in Engineering, Article ID 6843923, Volume 2018 (2018).

127. Chavolla, E., Valdivia, A., Diaz, P., Zaldivar, D., Cuevas, E., & Perez, M. A. (2018). Improved Unsupervised Color Segmentation Using a Modified HSV Color Model and a Bagging Procedure in K‐Means++ Algorithm. Mathematical Problems in Engineering, 2018(1), 2786952.

128. Octavio Camarena, Erik Cuevas, Marco Pérez-Cisneros, Fernando Fausto, Adrián González, and Arturo Valdivia, Ls-II: An Improved Locust Search Algorithm for Solving Optimization Problems, Mathematical Problems in Engineering, Article ID 4148975, Volume 2018 (2018).

129. Barocio, E., Regalado, J., Cuevas, E., Zúñiga, P., Torres, P.J.R., Modified bio-inspired optimisation algorithm with a centroid decision making approach for solving a multi-objective optimal power flow problem, IET Generation, Transmission and Distribution 11 (4), (2017), 1012-1022.

130. Fausto, F., Cuevas, E., Gonzales, A., A new descriptor for image matching based on bionic principles, Pattern Analysis and Applications, 20(4), (2017), 1245–125.

131. Cuevas, E., Luque, A., Zaldívar, D., Pérez-Cisneros, M., Evolutionary calibration of fractional fuzzy controllers, Applied Intelligence, 47(2), (2017), 291–303.

132. Diego Oliva, Salvador Hinojosa, Erik Cuevas, Gonzalo Pajares, Omar Avalos, Jorge Gálvez. Cross entropy based thresholding for magnetic resonance brain images using Crow Search Algorithm, Expert Systems with Applications, 79, (2017), 164-180.

133. Galvez J., Cuevas E., Avalos O., Flower Pollination Algorithm for Multimodal Optimization, International Journal of Computational Intelligence Systems, 10, (2017), 627–646.

134. Arturo Valdivia-Gonzalez, Daniel Zaldívar, Fernando Fausto, Octavio Camarena, Erik Cuevas and Marco Perez-Cisneros, A States of Matter Search-Based Approach for Solving the Problem of Intelligent Power Allocation in Plug-in Hybrid Electric Vehicles, Energies 2017, 10(1), 92.

135. Adrián González, Erik Cuevas, Fernando Fausto, Arturo Valdivia Raúl Rojas, A template matching approach based on the behavior of swarms of locust, Applied Intelligence, 47(4), (2017), 1087–1098.

136. Gurubel, K.J., Osuna-Enciso, V., Coronado-Mendoza, A., Cuevas, E. 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), (2017), 033101.

137. Arturo Valdivia-González, Daniel Zaldívar, Erik Cuevas, Marco Pérez-Cisneros, Fernando Fausto and Adrián González, A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells, Energies 2017, 10(7), 1052.

138. Díaz-Cortés, M.A., Cuevas, E., Gálvez, J., Camarena, O., A new metaheuristic optimization methodology based on fuzzy logic, Applied Soft Computing Journal, 61, (2017) 549-569.

139. Fausto, F., Cuevas, E., Valdivia, A., González, A., A global optimization algorithm inspired in the behavior of selfish herds, BioSystems, 160, (2017), 39-55.

140. Oliva, D., Hinojosa, S., Osuna-Enciso, V., Cuevas, E., Pérez-Cisneros, M., Sanchez-Ante, G,. Image segmentation by minimum cross entropy using evolutionary methods, Soft Computing, 1-20, (2017), In press.

141. Cuevas, E., Gálvez, J., Avalos, O., Parameter estimation for chaotic fractional systems by using the locust search algorithm, Computacion y Sistemas, 21(2), (2017), 369-380.

142. Valentín Osuna-Enciso, Erik Cuevas, Humberto Sossa, Diego Oliva, Marco Pérez-Cisneros, A bio-inspired evolutionary algorithm: A bio-inspired evolutionary algorithm: allostatic optimisation, International Journal of Bio-Inspired Computation, 8(3), (2016), 154 – 169.

143. Valentin Osuna-Enciso, Erik Cuevas, Diego Oliva, Virgilio Zúñiga, Marco Perez-Cisneros, and Daniel Zaldivar , A Multiobjective Approach to Homography Estimation, Computational Intelligence and Neuroscience, Volume 2016, Article ID 3629174, 12 pages.

144. Erik Cuevas, Eduardo Santuario, Daniel Zaldivar & Marco Perez-Cisneros, An improved evolutionary algorithm for reducing the number of function evaluations, Intelligent Automation & Soft Computing, 22(2), (2016), 177-192.

145. Erik Cuevas, Daniel Zaldívar, Gonzalo Pajares, Marco Perez-Cisneros, and Raúl Rojas, Computational Intelligence in Image Processing 2016, Mathematical Problems in Engineering Volume 2016 (2016), Article ID 5680246.

146. Omar Avalos, Erik Cuevas and Jorge Gálvez. Induction Motor Parameter Identification Using a Gravitational Search Algorithm. Computers 5(2), (2016), 6.

147. E Cuevas, V Osuna-Enciso, D Oliva. Circle detection on images based on the Clonal Selection Algorithm (CSA), The Imaging Science Journal, 63(1), (2015), 34-44.

148. Diego Oliva, Valentín Osuna-Enciso, Erik Cuevas, Daniel Zaldivar, Marco Perez, Improving segmentation velocity using an evolutionary method, Expert Systems With Applications, 42(14), (2015), 5874–5886.

149. Erik Cuevas, Adrián González, Daniel Zaldívar and Marco Pérez-Cisneros, An optimisation algorithm based on the behaviour of locust swarms, International Journal of Bio-Inspired Computation, (2015), 7(6), (2015), 402 – 407.

150. Erik Cuevas, Artificial Bee Colony (ABC) algorithm and its use in digital image processing, Iberoamerican Journal of Artificial Intelligence, 18(55), (2015), 50-68.

151. Marco Perez-Cisneros, Gerardo Garcia-Gil, Sabrina Vega-Maldonado, J. Arámburo-Lizárraga, Erik Cuevas, and Daniel Zaldivar, Applying BAT Evolutionary Optimization to Image-Based Visual Servoing, Mathematical Problems in Engineering, vol. 2015, Article ID 590138, 11 pages, 2015.

152. Erik Cuevas, Adrián González, Fernando Fausto, Daniel Zaldívar, and Marco Pérez-Cisneros, Multithreshold Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms, Mathematical Problems in Engineering, vol. 2015, Article ID 805357, 25 pages, 2015.

153. Erik Cuevas, Daniel Zaldívar, Gonzalo Pajares, Marco Perez-Cisneros, and Raúl Rojas, Computational Intelligence in Image Processing 2014, Mathematical Problems in Engineering, vol. 2015, Article ID 782826, 3 pages, 2015.

154. Erik Cuevas and Margarita Díaz, A Method for Estimating View Transformations from Image Correspondences Based on the Harmony Search Algorithm, Computational Intelligence and Neuroscience, vol. 2015, Article ID 434263, 15 pages, 2015.

155. Cuevas, E., Cienfuegos, M. A new algorithm inspired in the behavior of the social-spider for constrained optimization, Expert Systems with Applications, 41 (2), (2014), pp. 412-425.

156. Ramírez-Ortegón, M.A., Ramírez-Ramírez, L.L., Messaoud, I.B., Märgner, V., Cuevas, E., Rojas, R. 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), (2014), 139-160.

157. Cuevas, E., Echavarría, A., Ramírez-Ortegón, M.A. An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation, Applied Intelligence, 40(2) , (2014), 256-272.

158. Cuevas, E., González, M., Zaldívar, D., Pérez-Cisneros, M. Multi-ellipses detection on images inspired by collective animal behaviour, Neural Computing and Applications, 24(5), (2014), 1019-1033.

159. Sossa-Azuela H., Rubio E., Santiago R., López A., Peña A., Cuevas E. Alternative formulations to compute the binary shape Euler number, IET Computer Vision 8(3), 2014, 171 – 181.

160. Marte A. Ramírez-Ortegóna, Lilia L. Ramírez-Ramíreze, Volker Märgner, Ines Ben Messaoud, Erik Cuevas, Raúl Rojas, An analysis of the transition proportion for binarization in handwritten historical documents, Pattern Recognition, 47(8), (2014), 2635–2651.

161. Diego Oliva, Erik Cuevas, Gonzalo Pajares, Daniel Zaldivar, Valentín Osuna. A Multilevel Thresholding algorithm using electromagnetism optimization, Neurocomputing, 139, (2014), 357-381.

162. Diego Oliva, Erik Cuevas, Gonzalo Pajares. Parameter identification of solar cells using artificial bee colony optimization, Energy, 72, (2014), 93-102.

163. Diego Oliva, Erik Cuevas, Gonzalo Pajares, Daniel Zaldivar. Template Matching using an improved Electromagnetism-Like algorithm, Applied Intelligence, 41(3), (2014), 791-807.

164. Cuevas E., Reyna-Orta A. A Cuckoo Search algorithm for multimodal optimization, The Scientific World Journal, Vol 2014, 1-20.

165. Erik Cuevas, Jorge Gálvez, Salvador Hinojosa, Omar Avalos, Daniel Zaldívar and Marco Pérez-Cisneros. A Comparison of Evolutionary Computation Techniques for IIR Model Identification, Journal of Applied Mathematics, Volume 2014 (2014), Article ID 827206.

166. Ramírez-Ortegón, M.A., Märgner, V., Cuevas, E., Rojas, R. An optimization for binarization methods by removing binary artifacts, Pattern Recognition Letters, 34 (11), (2013), 1299-1306.

167. Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., Perez-Cisneros, M. Multilevel thresholding segmentation based on harmony search optimization, Journal of Applied Mathematics, 2013, art. no. 575414.

168. Cuevas, E., Cienfuegos, M., Zaldívar, D., Pérez-Cisneros, M. A swarm optimization algorithm inspired in the behavior of the social-spider, Expert Systems with Applications, 40(16), (2013), 6374-6384.

169. Cuevas, E., Echavarría, A., Zaldívar, D., Pérez-Cisneros, M. A novel evolutionary algorithm inspired by the states of matter for template matching, Expert Systems with Applications, 40 (16), (2013), 6359-6373.

170. Cuevas, E. Block-matching algorithm based on harmony search optimization for motion estimation, Applied Intelligence, 39 (1), (2013), 165-183.

171. Cuevas, E., González, M. Multi-circle detection on images inspired by collective animal behaviour, Applied Intelligence, 39 (1), (2013), 01-120.

172. Cuevas, E., Díaz, M., Manzanares, M., Zaldivar, D., Perez-Cisneros, M. An improved computer vision method for white blood cells detection, Computational and Mathematical Methods in Medicine, 2013 , art. no. 137392.

173. Cuevas, E., Zaldívar, D., Pérez-Cisneros, M. A swarm optimization algorithm for multimodal functions and its application in multicircle detection, Mathematical Problems in Engineering, 2013 , art. no. 948303.

174. Zaldivar, D., Cuevas, E., Pérez-Cisneros, M., Sossa, J., Rodríguez, J., Palafox, E. An educational fuzzy-based control platform using LEGO robots, International Journal of Electrical Engineering Education, 50 (2), (2013), 157-171.

175. Cuevas, E., Oliva, D., Díaz, M., Zaldivar, D., Pérez-Cisneros, M., Pajares, G. White blood cell segmentation by circle detection using electromagnetism-like optimization, Computational and Mathematical Methods in Medicine, 2013 , art. no. 395071.

176. Osuna-Enciso, V., Cuevas, E., Sossa, H. A comparison of nature inspired algorithms for multi-threshold image segmentation, Expert Systems with Applications, 40 (4), (2013), 1213-1219.

177. Cuevas, E., Zaldívar, D., Pérez-Cisneros, M., Oliva, D. Block-matching algorithm based on differential evolution for motion estimation, Engineering Applications of Artificial Intelligence, 26 (1) , (2013), 488-498.

178. Cuevas, E., Zaldívar, D., Pérez-Cisneros, M., Sossa, H., Osuna, V. Block matching algorithm for motion estimation based on Artificial Bee Colony (ABC), Applied Soft Computing Journal 13 (6), (2013), 3047-3059.

179. Cuevas, E., González, M. An optimization algorithm for multimodal functions inspired by collective animal behaviour, Soft Computing 17 (3) , (2013), 489-502.

180. Cuevas, E., Ortega-Sánchez, N., Zaldivar, D., Pérez-Cisneros, M. Circle detection by Harmony Search Optimization, Journal of Intelligent and Robotic Systems: Theory and Applications 66 (3), (2013), 359-376.

181. Erik Cuevas, Daniel Zaldívar, Gonzalo Pajares, Marco Perez-Cisneros, and Raul Rojas. Computational Intelligence in Image Processing, Mathematical Problems in Engineering, Volume 2013 (2013), Article ID 530404, 3 pages.

182. Cuevas, E., Zaldivar, D., Perez, M., Sanchez, E.N. LVQ neural networks applied to face segmentation, Intelligent Automation and Soft Computing 15 (3), (2013), 439-450.

183. Cuevas E., Oliva D. IIR Filter Modeling Using an Algorithm Inspired on Electromagnetism, Ingeniería Investigación y Tecnología, 14(1), (2013),125-138. (In Spanish).

184. Cuevas E., Ortega N., El algoritmo de búsqueda armónica y sus usos en el procesamiento digital de imágenes, Computacion y Sistemas, 17(4), (2013), 543-560.

185. Cuevas E., Santuario E., Zaldívar D., Perez-Cisneros M. Automatic Circle Detection on Images Based on an Evolutionary Algorithm That Reduces the Number of Function Evaluations, Mathematical Problems in Engineering, 2013, Article ID 868434, 17 pages.

186. Cuevas, E., Oliva, D., Zaldivar, D., Perez-Cisneros, M., Pajares, G. Opposition-based electromagnetism-like for global optimization, International Journal of Innovative Computing, Information and Control, 8 (12) , (2012), 8181-8198.

187. Cuevas, E., Wario, F., Osuna-Enciso, V., Zaldivar, D., Pérez-Cisneros, M. Fast algorithm for multiple-circle detection on images using learning automata, IET Image Processing 6 (8), (2012), 1124-1135.

188. Cuevas, E., Sención, F., Zaldivar, D., Pérez-Cisneros, M., Sossa, H. A multi-threshold segmentation approach based on artificial bee colony optimization, Applied Intelligence, 37 (3), (2012), 321-336.

189. Cuevas, E., Osuna-Enciso, V., Zaldivar, D., Pérez-Cisneros, M., Sossa, H. Multithreshold segmentation based on artificial immune Systems, Mathematical Problems in Engineering 2012 , art. no. 874761.

190. Cuevas, E., González, M., Zaldivar, D., Pérez-Cisneros, M., García, G. An algorithm for global optimization inspired by collective animal behaviour, Discrete Dynamics in Nature and Society 2012 , art. no. 638275.

191. Cuevas, E., Wario, F., Zaldivar, D., Pérez-Cisneros, M. Circle detection on images using learning automata, IET Computer Vision 6 (2), (2012), 121-132.

192. Cuevas, E., Sención-Echauri, F., Zaldivar, D., Pérez-Cisneros, M. Multi-circle detection on images using artificial bee colony (ABC) optimization, Soft Computing 16 (2), (2012), 281-296.

193. Cuevas, E., Oliva, D., Zaldivar, D., Pérez-Cisneros, M., Sossa, H. Circle detection using electro-magnetism optimization, Information Sciences 182 (1), (2012), 40-55.

194. Cuevas, E., Osuna-Enciso, V., Wario, F., Zaldívar, D., Pérez-Cisneros, M. Automatic multiple circle detection based on artificial immune systems, Expert Systems with Applications 39 (1), (2012), 713-722.

195. Cuevas, E., Zaldivar, D., Pérez-Cisneros, M., Sánchez, E., Ramírez-Ortegón, M. Robust fuzzy corner detector, Intelligent Automation and Soft Computing, 17 (4), (2011), 415-429.

196. Ramírez-Ortegón, M.A., Duéñez-Guzmán, E.A., Rojas, R., Cuevas, E. Unsupervised measures for parameter selection of binarization algorithms, Pattern Recognition 44 (3), (2011), 491-502.

197. Cuevas, E., Zaldivar, D., Pérez-Cisneros, M., Ramírez-Ortegón, M, Circle detection using discrete differential evolution optimization, Pattern Analysis and Applications, 14 (1), (2011), 93-107.

198. Cuevas, E., Zaldivar, D., Pérez-Cisneros, M., Ramirez-Ortegon, M. Hands-on experiments on intelligent behaviour for mobile robots, International Journal of Electrical Engineering Education 48 (1), (2011), 66-78.

199. Cuevas, E., Zaldivar, D., Pérez-Cisneros, M. Seeking multi-thresholds for image segmentation with Learning Automata, Machine Vision and Applications, 22 (5), (2011), 805-818.

200. Sossa H., Cuevas E, Zaldivar D. Alternative Way to Compute the Euler Number of a Binary Image, Journal of Applied Research and Technology, 9(3), (2011), 335-341.

201. Cuevas E., Osuna-Enciso V., Oliva D., Wario F. Circle Detection Using an Electromagnetism-Inspired Algorithm, Ingeniería Investigación y Tecnología., 12(4), (2011), 469-485. (In Spanish).

202. Cuevas, E., Zaldivar, D., Pérez-Cisneros, M., Ramírez-Ortegón, M. Polynomial trajectory algorithm for a biped robot, International Journal of Robotics and Automation 25 (4), (2010), 294-303.

203. Ramírez-Ortegón, M.A., Tapia, E., Rojas, R., Cuevas, E. Transition thresholds and transition operators for binarization and edge detection, Pattern Recognition 43 (10), (2010), 3243-3254.

204. Cuevas, E., Zaldivar, D., Pérez-Cisneros, M. Low-cost commercial Lego™ platform for mobile robotics, International Journal of Electrical Engineering Education 47 (2), (2010), 132-150.

205. Ramírez-Ortegón, M.A., Tapia, E., Ramírez-Ramírez, L.L., Rojas, R., Cuevas, E. Transition pixel: A concept for binarization based on edge detection and gray-intensity histograms, Pattern Recognition 43 (4), (2010), 1233-1243.

206. Sossa H., Cuevas E, Zaldivar D. Computation of the Euler Number of a Binary Image Composed of Hexagonal Cells, Journal of Applied Research and Technology, 8(3), (2010), 1665-6423.

207. Cuevas E., Osuna-Enciso V., Oliva D., Wario F., Zaldivar D. Segmentación y detección de glóbulos blancos en imágenes usando Sistemas Inmunes Artificiales, Revista Mexicana de Ingeniería Biomédica 31(2), (2010), 119-134. (In Spanish).

208. Cuevas E., Zaldivar D., Perez-Cisneros M., Tapia E. Generation and Optimization of Fuzzy Controllers Using the NEFCON Model, Computacion y Sistemas 14(2), (2010), 1405-5546. (In Spanish).

209. Cuevas, E., Zaldivar, D., Pérez-Cisneros, M. A novel multi-threshold segmentation approach based on differential evolution optimization, Expert Systems with Applications 37 (7), (2010), 5265-5271.

210. Cuevas, E., Zaldivar, D., Rojas, R. Neurofuzzy prediction for gaze control, Canadian Journal of Electrical and Computer Engineering 34 (1), (2009), 15-20.