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Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)

This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Gravitational Algorithm (SKF-GSA), for continuous numerical optimization problems. Simulated Kalman filter (SKF) was inspired by the estimation capability of Kalman filter. Every agent in SKF is regarded as a K...

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Main Authors: Badaruddin, Muhammad, Zuwairie, Ibrahim, Kamil Zakwan, Mohd Azmi, Khairul Hamimah, Abas, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd Aziz, Mohd Saberi, Mohamad
Format: Conference or Workshop Item
Language:English
Published: Universiti Malaysia Pahang 2016
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/15725/1/P115%20pg854-864.pdf
http://umpir.ump.edu.my/id/eprint/15725/
http://ee.ump.edu.my/ncon/wp-content/uploads/2016/10/Proceeding-NCON-PGR-2016.zip
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spelling my.ump.umpir.157252017-08-22T07:09:06Z http://umpir.ump.edu.my/id/eprint/15725/ Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA) Badaruddin, Muhammad Zuwairie, Ibrahim Kamil Zakwan, Mohd Azmi Khairul Hamimah, Abas Nor Azlina, Ab. Aziz Nor Hidayati, Abd Aziz Mohd Saberi, Mohamad TK Electrical engineering. Electronics Nuclear engineering This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Gravitational Algorithm (SKF-GSA), for continuous numerical optimization problems. Simulated Kalman filter (SKF) was inspired by the estimation capability of Kalman filter. Every agent in SKF is regarded as a Kalman filter. Inspired by the Newtonian gravitational law,gravitational search algorithm (GSA) has been introduced in 2009. Four methods (models) to hybridize SKF and GSA are proposed in this paper. The performance of the hybrid SKF-GSA algorithms is compared against the original SKF using CEC2014 benchmark dataset for continuous numerical optimization problems. Based on the analysis of experimental results, we found that model 3 and model 4 are performed better than the original SKF. Universiti Malaysia Pahang 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/15725/1/P115%20pg854-864.pdf Badaruddin, Muhammad and Zuwairie, Ibrahim and Kamil Zakwan, Mohd Azmi and Khairul Hamimah, Abas and Nor Azlina, Ab. Aziz and Nor Hidayati, Abd Aziz and Mohd Saberi, Mohamad (2016) Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA). In: Proceedings of The National Conference for Postgraduate Research (NCON-PGR 2016), 24-25 September 2016 , Universiti Malaysia Pahang (UMP), Pekan, Pahang. pp. 854-864.. http://ee.ump.edu.my/ncon/wp-content/uploads/2016/10/Proceeding-NCON-PGR-2016.zip
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Badaruddin, Muhammad
Zuwairie, Ibrahim
Kamil Zakwan, Mohd Azmi
Khairul Hamimah, Abas
Nor Azlina, Ab. Aziz
Nor Hidayati, Abd Aziz
Mohd Saberi, Mohamad
Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
description This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Gravitational Algorithm (SKF-GSA), for continuous numerical optimization problems. Simulated Kalman filter (SKF) was inspired by the estimation capability of Kalman filter. Every agent in SKF is regarded as a Kalman filter. Inspired by the Newtonian gravitational law,gravitational search algorithm (GSA) has been introduced in 2009. Four methods (models) to hybridize SKF and GSA are proposed in this paper. The performance of the hybrid SKF-GSA algorithms is compared against the original SKF using CEC2014 benchmark dataset for continuous numerical optimization problems. Based on the analysis of experimental results, we found that model 3 and model 4 are performed better than the original SKF.
format Conference or Workshop Item
author Badaruddin, Muhammad
Zuwairie, Ibrahim
Kamil Zakwan, Mohd Azmi
Khairul Hamimah, Abas
Nor Azlina, Ab. Aziz
Nor Hidayati, Abd Aziz
Mohd Saberi, Mohamad
author_facet Badaruddin, Muhammad
Zuwairie, Ibrahim
Kamil Zakwan, Mohd Azmi
Khairul Hamimah, Abas
Nor Azlina, Ab. Aziz
Nor Hidayati, Abd Aziz
Mohd Saberi, Mohamad
author_sort Badaruddin, Muhammad
title Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
title_short Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
title_full Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
title_fullStr Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
title_full_unstemmed Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
title_sort four different methods to hybrid simulated kalman filter (skf) with gravitational search algorithm (gsa)
publisher Universiti Malaysia Pahang
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/15725/1/P115%20pg854-864.pdf
http://umpir.ump.edu.my/id/eprint/15725/
http://ee.ump.edu.my/ncon/wp-content/uploads/2016/10/Proceeding-NCON-PGR-2016.zip
_version_ 1643667748909219840
score 13.211869

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