Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame Retardancy.

Nguyen, Hoang T; Nguyen, Kate T Q; Le, Tu C; Zhang, Guomin

Nguyen, Hoang T; Nguyen, Kate T Q; Le, Tu C; Zhang, Guomin.

Afiliación

Nguyen HT; Department of Infrastructure Engineering, School of Engineering, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia.
Nguyen KTQ; Department of Infrastructure Engineering, School of Engineering, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia.
Le TC; Manufacturing, Materials and Mechatronics, School of Engineering, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia.
Zhang G; Department of Infrastructure Engineering, School of Engineering, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia.

Molecules ; 26(4)2021 Feb 15.

Article en En | MEDLINE | ID: mdl-33672068

Asunto(s)

Inteligencia Artificial; Materiales de Construcción/análisis; Incendios/prevención & control; Retardadores de Llama/análisis; Aprendizaje Automático; Redes Neurales de la Computación

Palabras clave

artificial intelligence; chemical kinetics; combustion; flame retardants; machine learning; pyrolysis

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Materiales de Construcción / Incendios / Retardadores de Llama Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Australia

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