TY - GEN
T1 - Grey Wolf Optimizer Aided ANN Based Behavioral Modelling Scheme for Fully Printed VO2Switches
AU - Husain, Saddam
AU - Kanymkulov, Damir
AU - Akhmetov, Miras
AU - Nauryzbayev, Galymzhan
AU - Hashmi, Mohammad
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Radio Frequency (RF) switches are one of the key drivers in the modern design of Frequency-Reconfigurable Circuits (FRCs). Recently, fully printed Vanadium Dioxide (VO2) based RF switches have been proposed for the state-of-the-art FRCs. However, VO2 switch is still an evolving technology and needs behavioral models for the possible inclusion in computer aided design tools. This paper explores and develops Artificial Neural Network (ANN) and Grey Wolf Optimizer (GWO) aided ANN based behavioral models for the VO2 switch. Then, the models are thoroughly evaluated on common metrics namely mean squared error, mean absolute error, coefficient of determination, prediction ability on unseen data, training and simulation time, parameters' tuning time and complexity of the models.
AB - Radio Frequency (RF) switches are one of the key drivers in the modern design of Frequency-Reconfigurable Circuits (FRCs). Recently, fully printed Vanadium Dioxide (VO2) based RF switches have been proposed for the state-of-the-art FRCs. However, VO2 switch is still an evolving technology and needs behavioral models for the possible inclusion in computer aided design tools. This paper explores and develops Artificial Neural Network (ANN) and Grey Wolf Optimizer (GWO) aided ANN based behavioral models for the VO2 switch. Then, the models are thoroughly evaluated on common metrics namely mean squared error, mean absolute error, coefficient of determination, prediction ability on unseen data, training and simulation time, parameters' tuning time and complexity of the models.
KW - ANN
KW - behavioral modelling
KW - fully printed VO2 switch
KW - GWO
UR - https://www.scopus.com/pages/publications/85183578125
UR - https://www.scopus.com/pages/publications/85183578125#tab=citedBy
U2 - 10.1109/ICECS58634.2023.10382818
DO - 10.1109/ICECS58634.2023.10382818
M3 - Conference contribution
AN - SCOPUS:85183578125
T3 - ICECS 2023 - 2023 30th IEEE International Conference on Electronics, Circuits and Systems: Technosapiens for Saving Humanity
BT - ICECS 2023 - 2023 30th IEEE International Conference on Electronics, Circuits and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023
Y2 - 4 December 2023 through 7 December 2023
ER -