Publicaciones

ORCID: 0000-0001-8230-0098

google scholar: RA Conde-Gutierrez

scopus: 56047837800

Artículos 

  1. Cruz-Jacobo, U., Conde-Gutiérrez, R.A., Hernández, J.A., Silva-Martínez, S., Colorado, D., Juárez-Romero, D., Álvarez-Gallegos A. (2022). Optimization strategy to improve the removal efficiency of commercial herbicides using a multivariable inverse artificial neural network adapted with particle swarm optimization. Desalination and Water Treatment, 277, 90-104.
  2. Lounis, M., Torrealba-Rodriguez, O., & Conde-Gutiérrez, R. A. (2021). Predictive models for COVID-19 cases, deaths and recoveries in Algeria. Results in Physics30, 104845.
  3. Conde-Gutiérrez, R. A., Colorado, D., & Hernández-Bautista, S. L. (2021). Comparison of an artificial neural network and Gompertz model for predicting the dynamics of deaths from COVID-19 in México. Nonlinear Dynamics104(4), 4655-4669.
  4. Ajbar, W., Parrales, A., Cruz-Jacobo, U., Conde-Gutiérrez, R. A., Bassam, A., Jaramillo, O. A., & Hernández, J. A. (2021). The multivariable inverse artificial neural network combined with GA and PSO to improve the performance of solar parabolic trough collector. Applied Thermal Engineering189, 116651.
  5. Torrealba-Rodriguez, O., Conde-Gutiérrez, R. A., & Hernández-Javier, A. L. (2020). Modeling and prediction of COVID-19 in Mexico applying mathematical and computational models. Chaos, Solitons & Fractals138, 109946.
  6. Solís-Pérez, J. E., Gómez-Aguilar, J. F., Hernández, J. A., Escobar-Jiménez, R. F., Viera-Martin, E., Conde-Gutiérrez, R. A., & Cruz-Jacobo, U. (2019). Global optimization algorithms applied to solve a multi-variable inverse artificial neural network to improve the performance of an absorption heat transformer with energy recycling. Applied Soft Computing85, 105801.
  7. Conde-Gutiérrez, R. A., Cruz-Jacobo, U., Huicochea, A., Casolco, S. R., & Hernández, J. A. (2018). Optimal multivariable conditions in the operation of an absorption heat transformer with energy recycling solved by the genetic algorithm in artificial neural network inverse. Applied Soft Computing72, 218-234.
  8. Márquez-Nolasco, A., Conde-Gutiérrez, R. A., Hernández, J. A., Huicochea, A., Siqueiros, J., & Pérez, O. A. (2018). Optimization and estimation of the thermal energy of an absorber with graphite disks by using direct and inverse neural network. Journal of Energy Resources Technology140(2).
  9. Reyes-Téllez, E. D., Conde-Gutiérrez, R. A., Hernández, J. A., Cardoso, E., Silva-Martínez, S., Sierra, F. Z., & Cortés-Aburto, O. (2017). Optimal operating condition for a type parabolic trough collector with low-cost components using inverse neural network and solved by genetic algorithm. Desalination and Water Treatment73, 80-89.
  10. Morales, L. I., Conde-Gutiérrez, R. A., Hernández, J. A., Huicochea, A., Juárez-Romero, D., & Siqueiros, J. (2015). Optimization of an absorption heat transformer with two-duplex components using inverse neural network and solved by genetic algorithm. Applied Thermal Engineering85, 322-333.
  11. Bassam, A., Conde-Gutierrez, R. A., Castillo, J., Laredo, G., & Hernandez, J. A. (2014). Direct neural network modeling for separation of linear and branched paraffins by adsorption process for gasoline octane number improvement. Fuel124, 158-167.

Capítulos de libros

  1. R.A. Conde-Gutiérrez, U. Cruz-Jacobo & J.A. Hernández (2020). Use of Artificial Neural Networks in Optimizing Food Processes. En S. Sevda, A. Singh (Ed.), Mathematical and Statistical Applications in Food Engineering (321-345). CRC Press Taylor & Francis Group.
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