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dc.contributor.authorBadrzadeh, Honey
dc.contributor.supervisorDr Ranjan Sarukkalige
dc.contributor.supervisorProf. Amithirigala Jayawardena

In this research an attempt is made to develop highly accurate river flow forecasting models. Wavelet multi-resolution analysis is applied in conjunction with artificial neural networks and adaptive neuro-fuzzy inference system. Various types and structure of computational intelligence models are developed and applied on four different rivers in Australia. Research outcomes indicate that forecasting reliability is significantly improved by applying proposed hybrid models, especially for longer lead time and peak values.

dc.publisherCurtin University
dc.titleRiver flow forecasting using an integrated approach of wavelet multi-resolution analysis and computational intelligence techniques
curtin.departmentDepartment of Civil Engineering
curtin.accessStatusOpen access

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