MySQL database lookup table for Binary Particle Swarm optimization-based system identification

The NARX identification process is performed in two steps, namely model structure selection and parameter estimation. Structure selection involves selecting a subset of regressors to use that best describes the system. The structure selection task is a critical part of the system identification proc...

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Published in:ISIEA 2012 - 2012 IEEE Symposium on Industrial Electronics and Applications
Main Author: Yassin I.M.; Taib M.N.; Adnan R.; Salleh M.K.M.; Hamzah M.K.
Format: Conference paper
Language:English
Published: 2012
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876778363&doi=10.1109%2fISIEA.2012.6496641&partnerID=40&md5=57242d1bdab148cdd06935232296f95d
id 2-s2.0-84876778363
spelling 2-s2.0-84876778363
Yassin I.M.; Taib M.N.; Adnan R.; Salleh M.K.M.; Hamzah M.K.
MySQL database lookup table for Binary Particle Swarm optimization-based system identification
2012
ISIEA 2012 - 2012 IEEE Symposium on Industrial Electronics and Applications


10.1109/ISIEA.2012.6496641
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876778363&doi=10.1109%2fISIEA.2012.6496641&partnerID=40&md5=57242d1bdab148cdd06935232296f95d
The NARX identification process is performed in two steps, namely model structure selection and parameter estimation. Structure selection involves selecting a subset of regressors to use that best describes the system. The structure selection task is a critical part of the system identification process as the number of candidate structures grows exponentially with higher lag spaces. A Binary Particle Swarm based (BPSO) structure selected method has been implemented previously. However, the method was computationally expensive as QR factorization was required for each structure evaluation. Furthermore, redundant structures may be evaluated many times. Because of these problems, a database is proposed to store results of evaluated structures. The proposed method serves as a lookup table to reduce computational time for the BPSO algorithm. This paper describes the implementation of the proposed method, together with analysis of the stored database records on a DC motor dataset. © 2012 IEEE.


English
Conference paper

author Yassin I.M.; Taib M.N.; Adnan R.; Salleh M.K.M.; Hamzah M.K.
spellingShingle Yassin I.M.; Taib M.N.; Adnan R.; Salleh M.K.M.; Hamzah M.K.
MySQL database lookup table for Binary Particle Swarm optimization-based system identification
author_facet Yassin I.M.; Taib M.N.; Adnan R.; Salleh M.K.M.; Hamzah M.K.
author_sort Yassin I.M.; Taib M.N.; Adnan R.; Salleh M.K.M.; Hamzah M.K.
title MySQL database lookup table for Binary Particle Swarm optimization-based system identification
title_short MySQL database lookup table for Binary Particle Swarm optimization-based system identification
title_full MySQL database lookup table for Binary Particle Swarm optimization-based system identification
title_fullStr MySQL database lookup table for Binary Particle Swarm optimization-based system identification
title_full_unstemmed MySQL database lookup table for Binary Particle Swarm optimization-based system identification
title_sort MySQL database lookup table for Binary Particle Swarm optimization-based system identification
publishDate 2012
container_title ISIEA 2012 - 2012 IEEE Symposium on Industrial Electronics and Applications
container_volume
container_issue
doi_str_mv 10.1109/ISIEA.2012.6496641
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876778363&doi=10.1109%2fISIEA.2012.6496641&partnerID=40&md5=57242d1bdab148cdd06935232296f95d
description The NARX identification process is performed in two steps, namely model structure selection and parameter estimation. Structure selection involves selecting a subset of regressors to use that best describes the system. The structure selection task is a critical part of the system identification process as the number of candidate structures grows exponentially with higher lag spaces. A Binary Particle Swarm based (BPSO) structure selected method has been implemented previously. However, the method was computationally expensive as QR factorization was required for each structure evaluation. Furthermore, redundant structures may be evaluated many times. Because of these problems, a database is proposed to store results of evaluated structures. The proposed method serves as a lookup table to reduce computational time for the BPSO algorithm. This paper describes the implementation of the proposed method, together with analysis of the stored database records on a DC motor dataset. © 2012 IEEE.
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language English
format Conference paper
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record_format scopus
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