Data pre-processing combined with Artificial Neural Network to improve the performance of time series modelling

Document type:: Konferenzbeitrag
Contribution type:: Textbeitrag / Aufsatz
Author(s):: Duong, Tran Anh; Bui, Minh Duc; Rutschmann, Peter
Title:: Data pre-processing combined with Artificial Neural Network to improve the performance of time series modelling
Pages contribution:: 659-660
Chapter contribution:: Session: HM.3 Machine learning applied to hydraulic and hydrological modelling
Abstract:: Seasonal Decomposition (SD) and Discrete Wavelet Transform (DWT) techniques were linked into ANNs for predicting monthly rainfall in Ca-Mau province, Vietnam. Comparison between the calculated results using different models showed that the Meyer DWT combined with a Seasonal Artificial Neural Network (SANN) model provided the most accurate prediction.
Dewey Decimal Classification:: 620 Ingenieurwissenschaften
Editor:: Aronne Armanini and Elena Nucci
Book / Congress title:: New Challenges in hydraulic research and engineering. Proc. of the 5th IAHR-Europe Congress
Organization:: University of Trento, Italy and International Association for Hydro-Environment Engineering and Research (IAHR), Madrid, Spain
Date of congress:: 12 - 14 June, 2018
Publisher:: The International Association for Hydro-Environment Engineering and Research (IAHR)
Publisher address:: Madrid, Spain
Year:: 2018
E-ISBN:: 978-981-11-2731-1
Reviewed:: ja
Language:: en
Publication format:: WWW
WWW:: http://event.unitn.it/iahr2018
Format:: Text
BibTeX

Occurrences: