Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)

Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)

This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Particle Swarm Optimization (SKFPSO), 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...

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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/15726/
http://umpir.ump.edu.my/id/eprint/15726/
http://umpir.ump.edu.my/id/eprint/15726/1/P114%20pg843-853.pdf
id ump-15726
recordtype eprints
spelling ump-157262017-08-22T07:09:24Z http://umpir.ump.edu.my/id/eprint/15726/ Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO) 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 Particle Swarm Optimization (SKFPSO), 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 bird flocking, Particle Swarm Optimization (PSO), has been introduced in 1994.Four methods (models) to hybridize SKF and PSO are proposed in this paper. The performance of the hybrid SKF-PSO 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/15726/1/P114%20pg843-853.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 Particle Swarm Optimization (PSO). In: National Conference For Postgraduate Research (NCON-PGR 2016), 24-25 September 2016 , Universiti Malaysia Pahang, Pekan. pp. 843-853.. http://ee.ump.edu.my/ncon/wp-content/uploads/2016/10/Proceeding-NCON-PGR-2016.zip
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
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 Particle Swarm Optimization (PSO)
description This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Particle Swarm Optimization (SKFPSO), 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 bird flocking, Particle Swarm Optimization (PSO), has been introduced in 1994.Four methods (models) to hybridize SKF and PSO are proposed in this paper. The performance of the hybrid SKF-PSO 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 Particle Swarm Optimization (PSO)
title_short Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)
title_full Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)
title_fullStr Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)
title_full_unstemmed Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)
title_sort four different methods to hybrid simulated kalman filter (skf) with particle swarm optimization (pso)
publisher Universiti Malaysia Pahang
publishDate 2016
url http://umpir.ump.edu.my/id/eprint/15726/
http://umpir.ump.edu.my/id/eprint/15726/
http://umpir.ump.edu.my/id/eprint/15726/1/P114%20pg843-853.pdf
first_indexed 2023-09-18T22:20:42Z
last_indexed 2023-09-18T22:20:42Z
_version_ 1777415637119795200

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