BatTS: a hybrid method for optimizing deep feedforward neural network

Deep feedforward neural networks (DFNNs) have attained remarkable success in almost every computational task. However, the selection of DFNN architecture is still based on handcraft or hit-and-trial methods. Therefore, an essential factor regarding DFNN is about designing its architecture. Unfortuna...

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Detalles Bibliográficos
Autores principales: Pan, Sichen, Gupta, Tarun Kumar, Raza, Khalid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280266/
https://www.ncbi.nlm.nih.gov/pubmed/37346535
http://dx.doi.org/10.7717/peerj-cs.1194

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280266/
https://www.ncbi.nlm.nih.gov/pubmed/37346535
http://dx.doi.org/10.7717/peerj-cs.1194

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