Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/89828
Título: | Dimensional reduction applied to an intelligent model for boost converter switching operation |
Autor(es): | Fernandez-Serantes, Luis Alfonso Casteleiro-Roca, José Luis Novais, Paulo Simić, Dragan Calvo-Rolle, José Luis |
Palavras-chave: | Boost converter Classification Dimensional reduction Hard-switching Power electronics Soft-switching |
Data: | 2023 |
Editora: | Springer, Cham |
Revista: | Lecture Notes in Networks and Systems |
Citação: | Fernandez-Serantes, LA., Casteleiro-Roca, JL., Novais, P., Simić, D., Calvo-Rolle, J.L. (2023). Dimensional Reduction Applied to an Intelligent Model for Boost Converter Switching Operation. In: García Bringas, P., et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_12 |
Resumo(s): | The dimensional reduction algorithms are applied to a hybrid intelligent model that distinguishes the switching operating mode of a boost converter. Thus, the boost converter has been analyzed and both operating mode are explained, distinguishing between Hard-switching and Soft-switching modes. Then, the dataset is created out of the data obtained from simulation of the real circuit and the hybrid intelligent classification model is implemented. Finally, the dimensional reduction of the input variables is carried out and the results are compared. As result, the proposed model with the applied dimensional reduced dataset is able to distinguish between the HS and SS operating modes with high accuracy. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/89828 |
ISBN: | 978-3-031-18049-1 |
e-ISBN: | 978-3-031-18050-7 |
DOI: | 10.1007/978-3-031-18050-7_12 |
ISSN: | 2367-3370 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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SOCO22_V1.pdf | 261,37 kB | Adobe PDF | Ver/Abrir |