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Annals of nuclear energy v.113, 2018년, pp.75 - 88   SCI SCIE
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Artificial neural network approximations of linear fractional neutron models

Vyawahare, Vishwesh A. (Department of Electronics Engineering, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai 400 706, India ) ; Espinosa-Paredes, Gilberto (Área de Ingeniería en Recursos Energéticos, Universidad Autónoma Metropolitana-Iztapalapa, Av. San Rafael Atlixco 186, Col. Vicentina, Cd. de México 09340, Mexico ) ; Datkhile, Gaurav (Department of Electronics Engineering, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai 400 706, India ) ; Kadam, Pratik (Department of Electronics Engineering, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai 400 706, India ) ;
  • 초록  

    Abstract In this paper the artificial neural network (ANN) approximation for fractional neutron point kinetics (FNPK) model and fractional reduced-order model (F-ROM) is presented. The input-output data of the step response generated using the closed-loop stable fractional-order models was used for the training the ANN models. The ANN topology with various layers and different number of neutrons was tried to obtain the best approximation for the fractional-order model. The results confirm that the designed ANNs provide a good approximation to linear FNPK and F-ROM models. It was also observed that the convergence and learning of ANN is greatly affected by the type of model (FNPK or F-ROM), value of anomalous diffusion coefficient (fractional-order derivative) and the relaxation time. Highlights Linear model of fractional neutron point kinetics (FNPK) equations is discussed. Linear model of fractional reducer order model (F-ROM) is discussed. Artificial neural network (ANN) approximation for FNPK and F-ROM was analyzed. The input-output data of the step response of the closed-loop was used for training the ANN models. The ANN results can be used to carry out efficient simulation of linear models of FNPK and F-ROM.


  • 주제어

    Subdiffusive transport .   FNPK models .   Artificial neural networks .   Fractional Reduced Order Model (F-ROM).  

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