Evolutionary multi-objective optimization of extrusion barrier screws: data mining and decision making (2023)
- Authors:
- USP affiliated authors: DELBEM, ALEXANDRE CLÁUDIO BOTAZZO - ICMC ; MONACO, FRANCISCO JOSÉ - ICMC
- Unidade: ICMC
- DOI: 10.3390/polym15092212
- Subjects: ALGORITMOS GENÉTICOS; POLÍMEROS (MATERIAIS); MINERAÇÃO DE DADOS; TOMADA DE DECISÃO
- Keywords: polymer extrusion; barrier screws; multi-objective optimization; number of objectives reduction
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
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ABNT
GASPAR-CUNHA, António et al. Evolutionary multi-objective optimization of extrusion barrier screws: data mining and decision making. Polymers, v. 15, n. 9, p. 1-23, 2023Tradução . . Disponível em: https://doi.org/10.3390/polym15092212. Acesso em: 29 maio 2024. -
APA
Gaspar-Cunha, A., Costa, P., Delbem, A. C. B., Monaco, F. J., Ferreira, M. J., & José Covas,. (2023). Evolutionary multi-objective optimization of extrusion barrier screws: data mining and decision making. Polymers, 15( 9), 1-23. doi:10.3390/polym15092212 -
NLM
Gaspar-Cunha A, Costa P, Delbem ACB, Monaco FJ, Ferreira MJ, José Covas. Evolutionary multi-objective optimization of extrusion barrier screws: data mining and decision making [Internet]. Polymers. 2023 ; 15( 9): 1-23.[citado 2024 maio 29 ] Available from: https://doi.org/10.3390/polym15092212 -
Vancouver
Gaspar-Cunha A, Costa P, Delbem ACB, Monaco FJ, Ferreira MJ, José Covas. Evolutionary multi-objective optimization of extrusion barrier screws: data mining and decision making [Internet]. Polymers. 2023 ; 15( 9): 1-23.[citado 2024 maio 29 ] Available from: https://doi.org/10.3390/polym15092212 - Application of artificial intelligence techniques in the optimization of single screw polymer extrusion
- Caracterização do perfil de carga a partir de programas binários
- Many-objectives optimization: a machine learning approach for reducing the number of objectives
- Characterization of runtime resource usage from analysis of binary executable programs
- Multi-objective optimization of single screw polymer extrusion based on artificial intelligence
- Reducing the number of objectives for many objectives optimization: empirical analysis of a machine learning approach
- Genetic algorithm for the determination of linear viscoelastic relaxation spectrum from experimental data
- Artificial intelligence in single screw polymer extrusion: learning from computational data
- Caracterização do perfil de consumo de recursos de programas binários utilizando a técnica DAMICORE
- Regularization-free multicriteria optimization of polymer viscoelasticity model
Informações sobre o DOI: 10.3390/polym15092212 (Fonte: oaDOI API)
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