Agrawal, U., Soria, D., Wagner, C., Garibaldi, J., Ellis, I.O., Bartlett, J.M., Cameron, D., Rakha, E.A., Green, A.R., 2019. Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles. Artificial Intelligence in Medicine 97, 27 - 37. https://doi.org/10.1016/j.artmed.2019.05.002
Al-bayati, A.M.S., Alharbi, S.S., Alharbi, S.S., Matin, M., 2017. A comparative design and performance study of a non-isolated dc-dc buck converter based on si-mosfet/si-diode, sic-jfet/sic-schottky diode, and gan-transistor/sicschottky diode power devices, in: 2017 North American Power Symposium (NAPS), pp. 1-6. doi:10.1109/NAPS.2017.8107192. https://doi.org/10.1109/NAPS.2017.8107192
Beiranvand, R., Rashidian, B., Zolghadri, M.R., Alavi, S.M.H., 2011. Using llc resonant converter for designing wide-range voltage source. IEEE Transactions on Industrial Electronics 58, 1746-1756. doi:10.1109/TIE.2010.2052537. https://doi.org/10.1109/TIE.2010.2052537
[+]
Agrawal, U., Soria, D., Wagner, C., Garibaldi, J., Ellis, I.O., Bartlett, J.M., Cameron, D., Rakha, E.A., Green, A.R., 2019. Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles. Artificial Intelligence in Medicine 97, 27 - 37. https://doi.org/10.1016/j.artmed.2019.05.002
Al-bayati, A.M.S., Alharbi, S.S., Alharbi, S.S., Matin, M., 2017. A comparative design and performance study of a non-isolated dc-dc buck converter based on si-mosfet/si-diode, sic-jfet/sic-schottky diode, and gan-transistor/sicschottky diode power devices, in: 2017 North American Power Symposium (NAPS), pp. 1-6. doi:10.1109/NAPS.2017.8107192. https://doi.org/10.1109/NAPS.2017.8107192
Beiranvand, R., Rashidian, B., Zolghadri, M.R., Alavi, S.M.H., 2011. Using llc resonant converter for designing wide-range voltage source. IEEE Transactions on Industrial Electronics 58, 1746-1756. doi:10.1109/TIE.2010.2052537. https://doi.org/10.1109/TIE.2010.2052537
Düntsch, I., Gediga, G., 2020. Indices for rough set approximation and the application to confusion matrices. International Journal of Approximate Reasoning 118, 155 - 172. doi:https://doi.org/10.1016/j.ijar.2019.12.008 https://doi.org/10.1016/j.ijar.2019.12.008
Eraydin, H., Bakan, A.F., 2020. E ciency comparison of asynchronous and synchronous buck converter, in: 2020 6th International Conference on Electric Power and Energy Conversion Systems (EPECS), pp. 30-33. https://doi.org/10.1109/EPECS48981.2020.9304966
Fernandez-Serantes, L.A., Berger, H., Stocksreiter, W., Weis, G., 2016. Ultrahigh frequent switching with gan-hemts using the coss-capacitances as nondissipative snubbers, in: PCIM Europe 2016; International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, pp. 1-8.
GaN-Systems, 2018. GS66516T Top-side cooled 650 V E-mode GaN transistor. GaN Systems Inc. Rev 180422.
Gueguen, P., 2015. How power electronics will reshape to meet the 21st century challenges?, in: 2015 IEEE 27th International Symposium on Power Semiconductor Devices IC's (ISPSD), pp. 17-20. https://doi.org/10.1109/ISPSD.2015.7123378
Guillod, T., Papamanolis, P., W. Kolar, J., 2020. Artificial neural network (ann) based fast and accurate inductor modeling and design. IEEE Open Journal of Power Electronics 1, 284-299. doi:10.1109/OJPEL.2020.3012777. https://doi.org/10.1109/OJPEL.2020.3012777
Huang, G.C., Liang, T.J., Chen, K.H., 2012. Losses analysis and low standby losses quasi-resonant flyback converter design, in: 2012 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 217-220. https://doi.org/10.1109/ISCAS.2012.6271718
Kaski, S., Sinkkonen, J., Klami, A., 2005. Discriminative clustering. Neurocomputing 69, 18-41. https://doi.org/10.1016/j.neucom.2005.02.012
Li, Y., Ruan, X., Zhang, L., Dai, J., Jin, Q., 2019. Optimized parameters design and adaptive duty-cycle adjustment for class e dc-dc converter with on-off control. IEEE Transactions on Power Electronics 34, 7728-7744. https://doi.org/10.1109/TPEL.2018.2881170
Liu, M.Z., Shao, Y.H., Li, C.N., Chen, W.J., 2020. Smooth pinball loss nonparallel support vector machine for robust classification. Applied Soft Computing , 106840doi:https://doi.org/10.1016/j.asoc.2020.106840. https://doi.org/10.1016/j.asoc.2020.106840
Marchesan, G., Muraro, M., Cardoso, G., Mariotto, L., da Silva, C., 2016. Method for distributed generation anti-islanding protection based on singular value decomposition and linear discrimination analysis. Electric Power Systems Research 130, 124 - 131. https://doi.org/10.1016/j.epsr.2015.08.025
Mohan, N., Undeland, T.M., Robbins, W.P., 2003. Power electronics: converters, applications, and design. John wiley & sons.
Neumayr, D., Bortis, D., Kolar, J.W., 2020. The essence of the little box challenge-part a: Key design challenges solutions. CPSS Transactions on Power Electronics and Applications 5, 158-179. https://doi.org/10.24295/CPSSTPEA.2020.00014
Qin, A.K., Suganthan, P.N., 2005. Enhanced neural gas network for prototypebased clustering. Pattern recognition 38, 1275-1288. https://doi.org/10.1016/j.patcog.2004.12.007
Tahiliani, S., Sreeni, S., Moorthy, C.B., 2019. A multilayer perceptron approach to track maximum power in wind power generation systems, in: TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), pp. 587-591. doi:10.1109/TENCON.2019.8929414. https://doi.org/10.1109/TENCON.2019.8929414
Tao Liu, Wenjun Zhang, Zhiping Yu, 2005. Modeling of spiral inductors using artificial neural network, in: Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., pp. 2353-2358 vol. 4. doi:10.1109/IJCNN.2005.1556269.
Thapngam, T., Yu, S., Zhou, W., 2012. Ddos discrimination by linear discriminant analysis (lda), in: 2012 International Conference on Computing, Networking and Communications (ICNC), IEEE. pp. 532-536. https://doi.org/10.1109/ICCNC.2012.6167480
Tulbure, A., Kadar, M., 2017. Power electronics methods to improve energy effciency in the public transportation system, in: 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC), pp. 1277-1281. doi:10.1109/ICE.2017.8280027. https://doi.org/10.1109/ICE.2017.8280027
Uysal, I., G¨uvenir, H.A., 1999. An overview of regression techniques for knowledge discovery. The Knowledge Engineering Review 14, 319-340. https://doi.org/10.1017/S026988899900404X
Wang, Z., Lou, Z., Chen, H., 2007. A novel dual-llc resonant soft switching converter for super high frequency induction heating power supplies, in: 2007 IEEE Power Electronics Specialists Conference, pp. 2561-2566. https://doi.org/10.1109/PESC.2007.4342418
Wei, C., Zhang, Z., Qiao, W., Qu, L., 2015. Reinforcement-learning-based intelligent maximum power point tracking control for wind energy conversion systems. IEEE Transactions on Industrial Electronics 62, 6360-6370. https://doi.org/10.1109/TIE.2015.2420792
Whitaker, B., Barkley, A., Cole, Z., Passmore, B., McNutt, T., Lostetter, A.B., 2013. High-frequency ac-dc conversion with a silicon carbide power module to achieve high-effciency and greatly improved power density, in: 2013 4th IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG), pp. 1-5. doi:10.1109/PEDG.2013.6785611. https://doi.org/10.1109/PEDG.2013.6785611
Zhan, X., Wang, W., Chung, H., 2018. A neural-network-based color control method for multi-color led systems. IEEE Transactions on Power Electronics 34, 7900-7913. https://doi.org/10.1109/TPEL.2018.2880876
Zhao, S., Blaabjerg, F., Wang, H., 2021. An overview of artificial intelligence applications for power electronics. IEEE Transactions on Power Electronics 36, 4633-4658. doi:10.1109/TPEL.2020.3024914. https://doi.org/10.1109/TPEL.2020.3024914
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