eprintid: 2080
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/20/80
datestamp: 2023-11-09 15:50:15
lastmod: 2023-11-09 15:50:15
status_changed: 2023-11-09 15:41:58
type: conference_item
metadata_visibility: show
creators_name: Ismail, M.J.
creators_name: Ibrahim, R.
creators_name: Ismail, I.
title: Adaptive neural network prediction model for energy consumption
ispublished: pub
keywords: Adaptive models; Adaptive neural network models; Adaptive neural networks; Developed model; Dynamic prediction; Energy consumption; Energy prediction; Gas flows; Metering stations; Metering systems; Sliding Window; sliding window training method; Static neural networks; Training methods, Electric load forecasting; Energy utilization; Forecasting; Mathematical models, Neural networks
note: cited By 7; Conference of 2011 3rd International Conference on Computer Research and Development, ICCRD 2011 ; Conference Date: 11 March 2011 Through 15 March 2011; Conference Code:84959
abstract: This paper discusses on the adaptive neural network model for predicting the energy consumption at a metering station. The function of the metering system is to calculate the energy consumption of the outgoing gas flow. To ensure the robustness of the developed model, it is suggested to make the model an adaptive model that will periodically update the weights. This will ensure the reliability of the model. A dynamic prediction model that can adapt itself to changes in the energy consumption pattern is desirable especially for short-term energy prediction. It is also important for an on-line running of the metering system. Two methods of weights update are proposed and tested, namely the accumulative training and sliding window training. The developed adaptive neural network model is then compared with the static neural network. Adaptive neural network for energy consumption has shown better result and recommended for implementation in the metering station. © 2011 IEEE.
date: 2011
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79957536756&doi=10.1109%2fICCRD.2011.5763864&partnerID=40&md5=c91705abba258f3d32746fd9687258b6
id_number: 10.1109/ICCRD.2011.5763864
full_text_status: none
publication: ICCRD2011 - 2011 3rd International Conference on Computer Research and Development
volume: 4
place_of_pub: Shanghai
pagerange: 109-113
refereed: TRUE
isbn: 9781612848372
citation:   Ismail, M.J. and Ibrahim, R. and Ismail, I.  (2011) Adaptive neural network prediction model for energy consumption.  In: UNSPECIFIED.