Machine learning models for estimating contamination across different curbside collection strategies.

Runsewe, T; Damgacioglu, H; Perez, L; Celik, N

Runsewe, T; Damgacioglu, H; Perez, L; Celik, N.

Afiliación

Runsewe T; Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL, USA. Electronic address: tor9@miami.edu.
Damgacioglu H; Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, USA. Electronic address: damgacio@musc.edu.
Perez L; Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL, USA. Electronic address: lmp72@miami.edu.
Celik N; Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL, USA. Electronic address: celik@miami.edu.

J Environ Manage ; 340: 117855, 2023 Aug 15.

Article en En | MEDLINE | ID: mdl-37116416

Asunto(s)

Aprendizaje Automático; Modelos Estadísticos; Modelos Lineales; Máquina de Vectores de Soporte

Palabras clave

Curbside collection strategies; Efficient recycling; Inbound contamination; Paper contamination

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Modelos Estadísticos / Aprendizaje Automático Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Environ Manage Año: 2023 Tipo del documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google