A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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American Chemical Society
2025-03-01
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| Series: | ACS Engineering Au |
| Online Access: | https://doi.org/10.1021/acsengineeringau.5c00001 |
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| _version_ | 1849688526306672640 |
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| author | Matheus Máximo-Canadas Julio Cesar Duarte Jakler Nichele Leonardo Santos de Brito Alves Luiz Octavio Vieira Pereira Rogerio Ramos Itamar Borges |
| author_facet | Matheus Máximo-Canadas Julio Cesar Duarte Jakler Nichele Leonardo Santos de Brito Alves Luiz Octavio Vieira Pereira Rogerio Ramos Itamar Borges |
| author_sort | Matheus Máximo-Canadas |
| collection | DOAJ |
| format | Article |
| id | doaj-art-626bdf74977b4bccbf5fde3e34b7171e |
| institution | DOAJ |
| issn | 2694-2488 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | American Chemical Society |
| record_format | Article |
| series | ACS Engineering Au |
| spelling | doaj-art-626bdf74977b4bccbf5fde3e34b7171e2025-08-20T03:21:59ZengAmerican Chemical SocietyACS Engineering Au2694-24882025-03-015322623310.1021/acsengineeringau.5c00001A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of MethaneMatheus Máximo-Canadas0Julio Cesar Duarte1Jakler Nichele2Leonardo Santos de Brito Alves3Luiz Octavio Vieira Pereira4Rogerio Ramos5Itamar Borges6Departamento de Química, Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ, BrasilDepartamento de Computação, Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ, BrasilDepartamento de Química, Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ, BrasilLaboratório de Dinâmica dos Fluidos Computacional, Departamento de Engenharia Mecânica, Universidade Federal Fluminense (UFF), Niterói, RJ, BrasilCentro de Pesquisas, Desenvolvimento e Inovação Leopoldo Américo Miguez de Mello - CENPES/PETROBRAS Rua Avenida Horácio Macedo, Rio de Janeiro, RJ, BrasilCentro Tecnológico, Departamento de Engenharia Mecânica, Universidade Federal do Espírito Santo (UFES), Vitória, ES, BrasilDepartamento de Química, Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ, Brasilhttps://doi.org/10.1021/acsengineeringau.5c00001 |
| spellingShingle | Matheus Máximo-Canadas Julio Cesar Duarte Jakler Nichele Leonardo Santos de Brito Alves Luiz Octavio Vieira Pereira Rogerio Ramos Itamar Borges A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane ACS Engineering Au |
| title | A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane |
| title_full | A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane |
| title_fullStr | A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane |
| title_full_unstemmed | A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane |
| title_short | A Systematic and General Machine Learning Approach to Build a Consistent Data Set from Different Experiments: Application to the Thermal Conductivity of Methane |
| title_sort | systematic and general machine learning approach to build a consistent data set from different experiments application to the thermal conductivity of methane |
| url | https://doi.org/10.1021/acsengineeringau.5c00001 |
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