Comparative performance analysis of support vector regression and artificial neural network for prediction of municipal solid waste generation.

Jassim, Majeed S; Coskuner, Gulnur; Zontul, Metin

Jassim, Majeed S; Coskuner, Gulnur; Zontul, Metin.

Afiliação

Jassim MS; Department of Chemical Engineering, College of Engineering, University of Bahrain, Isa Town, Kingdom of Bahrain.
Coskuner G; Department of Chemical Engineering, College of Engineering, University of Bahrain, Isa Town, Kingdom of Bahrain.
Zontul M; Department of Computer Engineering, Faculty of Engineering and Architecture, Istanbul Arel University, Istanbul, Turkey.

Waste Manag Res ; 40(2): 195-204, 2022 Feb.

Article em En | MEDLINE | ID: mdl-33818220

Assuntos

Resíduos Sólidos; Gerenciamento de Resíduos; Algoritmos; Modelos Teóricos; Redes Neurais de Computação; Resíduos Sólidos/análise

Palavras-chave

Artificial intelligence; Bahrain; landfill; machine learning; multi-layer perceptron; municipal solid waste; predictive modelling; waste generation rate

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Resíduos Sólidos / Gerenciamento de Resíduos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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