TY - CHAP
T1 - A Comparison Study of Deep Learning Algorithms for Metasurface Harvester Designs
AU - Ajmi, Haitham Al
AU - Bait-Suwailam, Mohammed M.
AU - Khriji, Lazhar
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/6/19
Y1 - 2023/6/19
N2 - The paper compares three deep learning artificial intelligence algorithms used for metasurface design. In-house design code for designing metasurface structures was developed with Python, the NumPy library. To facilitate the study, the three algorithms used are AdaBelief, Adam, and Yogi. According to the numerical comparison study, Adam has a better performance in terms of model generalization with a large dataset (in our case 7000 samples), while Adabelief and Yogi show a better performance in terms of a low dataset (in our case 4,000 samples), and Yogi has a better performance with a lower dataset correlation between the predicted performance of the energy harvester obtained from three algorithms. Yogi and Adablief performance could be improved by manipulating the hyper-parameters.
AB - The paper compares three deep learning artificial intelligence algorithms used for metasurface design. In-house design code for designing metasurface structures was developed with Python, the NumPy library. To facilitate the study, the three algorithms used are AdaBelief, Adam, and Yogi. According to the numerical comparison study, Adam has a better performance in terms of model generalization with a large dataset (in our case 7000 samples), while Adabelief and Yogi show a better performance in terms of a low dataset (in our case 4,000 samples), and Yogi has a better performance with a lower dataset correlation between the predicted performance of the energy harvester obtained from three algorithms. Yogi and Adablief performance could be improved by manipulating the hyper-parameters.
KW - AdaBelief
KW - Adam
KW - Yogi
KW - deep learning
KW - metasurface
UR - http://www.scopus.com/inward/record.url?scp=85168339274&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85168339274&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/ee1aadee-6c7b-3d6c-b729-f22c9ab6e202/
U2 - 10.1109/iccns58795.2023.10193585
DO - 10.1109/iccns58795.2023.10193585
M3 - Chapter
AN - SCOPUS:85168339274
SN - 9798350339291
T3 - 2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)
SP - 74
EP - 78
BT - 2023 International Conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2023
A2 - Quwaider, Muhannad
A2 - Lloret, Jaime
A2 - Angelides, Marios C.
A2 - Jararweh, Yaser
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2023
Y2 - 19 June 2023 through 21 June 2023
ER -