eprintid: 1684
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/16/84
datestamp: 2023-11-09 15:49:51
lastmod: 2023-11-09 15:49:51
status_changed: 2023-11-09 15:41:08
type: conference_item
metadata_visibility: show
creators_name: Tawfeig, H.
creators_name: Asirvadam, V.S.
creators_name: Saad, N.
title: Sliding-window learning using MLP networks with data store management
ispublished: pub
keywords: Conjugate gradient algorithms; Correlated data; Data store; First order; Multi-layer perceptron neural networks; Multilayer Perceptron; Nonlinear conjugate gradient; Off-line learning; Offline data; Online learning; Second orders; Sliding-window; System variables; Time varying; Training algorithms, Algorithms; Backpropagation; Conjugate gradient method; Network management; Sustainable development, E-learning
note: cited By 2; Conference of 3rd National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011 ; Conference Date: 19 September 2011 Through 20 September 2011; Conference Code:88531
abstract: This paper explore the performance of sliding-window based for training multilayer perceptron neural network with correlated data. Online learning is usually employed when system variables are time varying. It is also used when it is not suitable to obtain a full history of offline data about the system as compared to offline learning. Sliding-window framework is proposed to combine the robustness of offline learning with the ability of online learning to track time varying elements of the process under investigation. This paper evaluates the performance of first order back propagation, second order conjugate gradient algorithms and the recent binary ensemble training algorithms with sliding-window learning routine. Different data store management techniques are presented to deal with the correlation problem. © 2011 IEEE.
date: 2011
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857074986&doi=10.1109%2fNatPC.2011.6136391&partnerID=40&md5=cb86c2c47968e0b6ab4e935847f449c7
id_number: 10.1109/NatPC.2011.6136391
full_text_status: none
publication: 2011 National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011
place_of_pub: Perak
refereed: TRUE
isbn: 9781457718847
citation:   Tawfeig, H. and Asirvadam, V.S. and Saad, N.  (2011) Sliding-window learning using MLP networks with data store management.  In: UNSPECIFIED.