Performance assessment of artificial neural networks and support vector regression models for stream flow predictions.

Ghumman, Abdul Razzaq; Ahmad, Sajjad; Hashmi, Hashim Nisar

Ghumman, Abdul Razzaq; Ahmad, Sajjad; Hashmi, Hashim Nisar.

Afiliação

Ateeq-Ur-Rauf; Faculty of Civil & Environmental Engineering, University of Engineering & Technology, Taxila, Pakistan.
Ghumman AR; Department of Civil Engineering, Bannu Campus, University of Engg & Tech, Peshawar, Pakistan.
Ahmad S; Faculty of Civil & Environmental Engineering, University of Engineering & Technology, Taxila, Pakistan. abdul.razzaq@qec.edu.sa.
Hashmi HN; College of Engineering, Civil Engineering Department, Qassim University, Buraydah, Saudi Arabia. abdul.razzaq@qec.edu.sa.

Environ Monit Assess ; 190(12): 704, 2018 Nov 08.

Article em En | MEDLINE | ID: mdl-30406854

Assuntos

Monitoramento Ambiental/métodos; Hidrologia/métodos; Redes Neurais de Computação; Rios; Movimentos da Água; Algoritmos; Inteligência Artificial; Paquistão; Máquina de Vetores de Suporte

Palavras-chave

Artificial neural network; Genetic algorithm; Indus River; Streamflow forecast; Support vector regression

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Movimentos da Água / Hidrologia / Monitoramento Ambiental / Redes Neurais de Computação / Rios Idioma: En Ano de publicação: 2018 Tipo de documento: Article

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