TY - GEN
T1 - Development of optimized RF cavity in 10 MeV cyclotron
AU - Mohamadian, M.
AU - Salehi, M.
AU - Afarideh, H.
AU - Ghergherehchi, M.
AU - Chai, Jong Seo
N1 - Publisher Copyright:
Copyright © 2016 CC-BY-3.0 and by the respective authors.
PY - 2016
Y1 - 2016
N2 - Cyclotron cavity modelled by an artificial neural network, which is trained by our optimized algorithm. The training samples are obtained from simulation results, which are done by MWS CST software for some defined situation and parameters, and also with the conventional BP algorithm. It is shown that the optimized FFN can estimate the cyclotron model parameters with acceptable outputs. Hence, the neural network trained by this algorithm represents the proper estimation and acceptable ability to our structure modelling. The cyclotron cavity parameter modelling illustrate that the neural network trained by the this algorithm could be the acceptable method to design parameters.
AB - Cyclotron cavity modelled by an artificial neural network, which is trained by our optimized algorithm. The training samples are obtained from simulation results, which are done by MWS CST software for some defined situation and parameters, and also with the conventional BP algorithm. It is shown that the optimized FFN can estimate the cyclotron model parameters with acceptable outputs. Hence, the neural network trained by this algorithm represents the proper estimation and acceptable ability to our structure modelling. The cyclotron cavity parameter modelling illustrate that the neural network trained by the this algorithm could be the acceptable method to design parameters.
UR - https://www.scopus.com/pages/publications/85015307006
M3 - Conference contribution
AN - SCOPUS:85015307006
T3 - IPAC 2016 - Proceedings of the 7th International Particle Accelerator Conference
SP - 1250
EP - 1252
BT - IPAC 2016 - Proceedings of the 7th International Particle Accelerator Conference
PB - Joint Accelerator Conferences Website (JACoW)
T2 - 7th International Particle Accelerator Conference, IPAC 2016
Y2 - 8 May 2016 through 13 May 2016
ER -