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Wavelet network: online sequential extreme learning machine for nonlinear dynamic systems identification


Citation

Mohammed Salih, Dhiadeen and Mohd Noor, Samsul Bahari and Marhaban, Mohammad Hamiruce and Raja Ahmad, Raja Mohd Kamil (2015) Wavelet network: online sequential extreme learning machine for nonlinear dynamic systems identification. Advances in Artificial Intelligence, 2015. art. no. 184318. pp. 1-10. ISSN 1687-7470

Abstract

A single hidden layer feedforward neural network (SLFN) with online sequential extreme learning machine (OSELM) algorithm has been introduced and applied in many regression problems successfully. However, using SLFN with OSELM as black-box for nonlinear system identification may lead to building models for the identified plant with inconsistency responses from control perspective. The reason can refer to the random initialization procedure of the SLFN hidden node parameters with OSELM algorithm. In this paper, a single hidden layer feedforward wavelet network (WN) is introduced with OSELM for nonlinear system identification aimed at getting better generalization performances by reducing the effect of a random initialization procedure.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1155/2015/184318
Publisher: Hindawi Publishing Corporation
Keywords: Wavelet network; Online sequential extreme learning machine; Nonlinear dynamic systems
Depositing User: Ms. Ainur Aqidah Hamzah
Date Deposited: 25 May 2022 03:43
Last Modified: 25 May 2022 03:43
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1155/2015/184318
URI: http://psasir.upm.edu.my/id/eprint/46889
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