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

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..

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Abstract

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.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Simulated Kalman Filter, Hybrid Simulated Kalman Filter, Continuous Numerical Optimization Problem
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Rosfadilla Mohamad Zainun
Date Deposited: 09 Dec 2016 06:26
Last Modified: 22 Aug 2017 07:09
URI: http://umpir.ump.edu.my/id/eprint/15726
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