Omar Avalos Alvarez

El Dr. Ávalos se tituló de la Licenciatura en Ingeniería en Comunicaciones y Electrónica, y de la Maestría y Doctorado en Ciencias en Ingeniería Electrónica y Computación en la Universidad de Guadalajara.

Actualmente es profesor en la División de Electrónica y Computación en el Centro Universitario de Ciencias Exactas e Ingenierías de la Universidad de Guadalajara. Asi mismo, el Dr. Avalos pertenece a la linea de investigación de Analitica de datos y aprendizaje maquina.

PRODUCCIÓN CIENTÍFICA

• Avalos, O., Ayala, E., Wario, F., Pérez-Cisneros, M.  An accurate Cluster chaotic optimization approach for digital medical image segmentation. Neural Comput & Applic 33, 10057–10091 (2021).
  • https://doi.org/10.1007/s00521-021-05771-8
• Avalos, O. (2020). GSA for machine learning problems: A comprehensive overview. Applied Mathematical Modelling, (92), 261-280. 
  • https://doi.org/10.1016/j.apm.2020.11.013
• Avalos, O., Cuevas, E., Becerra, H.G., ...Hinojosa, S., Zaldívar, D. (2021). Kernel Recursive Least Square Approach for Power System Harmonic Estimation. Electric Power Components and Systems , (48), 1708-1721,
  • https://doi.org/10.1080/15325008.2021.1908457
• Cuevas, E., Gálvez, J., Avalos, O., Chavarin, Á.. (2021). A mean shift segmentation scheme using several pixel characteristics. Computers & Electrical Engineering, (90), 107022.
  • https://doi.org/10.1016/j.compeleceng.2021.107022
• 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), 1226.
  • ​https://doi.org/10.3390/math8081226
• Gálvez, J., Cuevas, E., Becerra, H., Avalos, O. (2020) A hybrid optimization approach based on clustering and chaotic sequences. International Journal of Machine Learning and Cybernetics, (11), 359-401. 
  • https://doi.org/10.1007/s13042-019-00979-6​
• 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
• Avalos, O., Cuevas, E., Valdivia-González, A., ...Zaldívar, D., Oliva, D. (2019). A Comparative Study of Evolutionary Computation Techniques for Solar Cells Parameter Estimation. Computacion y Sistemas, (23), 231 - 256   DOI: 10.13053/CyS-23-1-2881
• Hinojosa, S., Avalos, O., Oliva, D., ...Zaldivar, D., Gálvez, J. (2018). Unassisted thresholding based on multi-objective evolutionary algorithms. Knowledge-Based Systems. (159), 221- 232. 
  • ​https://doi.org/10.1016/j.knosys.2018.06.028
• Gálvez, J., Cuevas, E., Avalos, O., Oliva, D., Hinojosa, S. Electromagnetism-like mechanism with collective animal behavior for multimodal optimization. Applied Intelligence (48), 2580 - 2612.
  • https://doi.org/10.1007/s10489-017-1090-1
• Hinojosa, S., Oliva, D., Cuevas, E. et al. Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm. Neural Comput & Applic 29, 319–335 (2018).
  • https://doi.org/10.1007/s00521-017-3251-x
• Díaz, P., Pérez-Cisneros, M., Cuevas, E., ...Hinojosa, S., Zaldivar, D. An Improved Crow Search Algorithm Applied to Energy Problems. Energies. (11), 571. 
  • https://doi.org/10.3390/en11030571
• Cuevas, E., Díaz, P., Avalos, O. et al. Nonlinear system identification based on ANFIS-Hammerstein model using Gravitational search algorithm. Appl Intell 48, 182–203 (2018). 
  • https://doi.org/10.1007/s10489-017-0969-1​.
• Oliva, D., Hinojosa, S., Cuevas, E., ...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. 
  • https://doi.org/10.1016/j.eswa.2017.02.042
• Cuevas, E., Gálvez, J., Avalos, O.Parameter estimation for chaotic fractional systems by using the locust search algorithm. Computacion y Sistemas. (21), 369 - 380. DOI:  10.13053/CyS-21-2-2741​
• Gálvez, J., Cuevas, E., Avalos,O. Flower Pollination Algorithm for multimodal optimization. International Journal of Computational Intelligence Systems, (10), 627 - 646. 
  • https://doi.org/10.2991/ijcis.2017.10.1.42
• Avalos, O., Cuevas, E., Gálvez, J. Induction motor parameter identification using a gravitational search algorithm. Computers. (5), 6.
  • ​https://doi.org/10.3390/computers5020006
• ​Cuevas, E., Gálvez, J., Hinojosa, S., ...Zaldívar, D., Pérez-Cisneros, M. A comparison of evolutionary computation techniques for IIR model identification. (2014), 827206.
  • https://doi.org/10.1155/2014/827206
• Wario, F, Avalos, O, Gálvez, J. (2021). Biosignal Processing and Classification Using Computational Learning and Intelligence. Bio-inspired Algorithms México : ACADEMIC PR INC

LIBROS

• Cuevas, E., Avalos , O., Diaz, P., Valdivia, A., Pérez, M. (2021). Introducción al machine learning con matlab . España: Marcombo
• Cuevas E., Gálvez J., Avalos O. (2020) Comparison of Solar Cells Parameters Estimation Using Several Optimization Algorithms. In: Recent Metaheuristics Algorithms for Parameter Identification. Studies in Computational Intelligence, vol 854. Springer, Cham.
  • https://doi.org/10.1007/978-3-030-28917-1_4

CAPITULOS DE LIBROS

• Chavarin Á., Gálvez J., Avalos O. (2020) Image Thresholding with Metaheuristic Algorithms for Cerebral Injuries. In: Oliva D., Hinojosa S. (eds) Applications of Hybrid Metaheuristic Algorithms for Image Processing. Studies in Computational Intelligence, vol 890. Springer, Cham.
  • https://doi.org/10.1007/978-3-030-40977-7_20

PARTICIPACIÓN Y CONGRESOS

Hinojosa, S., Avalos, O., Gálvez, J., Oliva, D., Cuevas, E., & Pérez-Cisneros, M. (2018, November). Remote sensing imagery segmentation based on multi-objective optimization algorithms. In 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1-6). IEEE.