A framework for predicting odor threshold values of perfumes by scientific machine learning and transfer learning.

Oliveira, Luis M C; Santana, Vinícius V; Rodrigues, Alírio E; Ribeiro, Ana M; B R Nogueira, Idelfonso

Oliveira, Luis M C; Santana, Vinícius V; Rodrigues, Alírio E; Ribeiro, Ana M; B R Nogueira, Idelfonso.

Afiliación

Oliveira LMC; LSRE-LCM - Laboratory of Separation and Reaction Engineering - Laboratory of Catalysis and Materials, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal.
Santana VV; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal.
Rodrigues AE; LSRE-LCM - Laboratory of Separation and Reaction Engineering - Laboratory of Catalysis and Materials, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal.
Ribeiro AM; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal.
B R Nogueira I; LSRE-LCM - Laboratory of Separation and Reaction Engineering - Laboratory of Catalysis and Materials, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal.

Heliyon ; 9(10): e20813, 2023 Oct.

Article en En | MEDLINE | ID: mdl-37867888

Palabras clave

Artificial neural networks; Feedforward neural networks; Graph convolutional networks; Machine learning; Odor thresholds; Transfer learning

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article País de afiliación: Portugal Pais de publicación: Reino Unido

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