A Hybrid Simulated Kalman Filter - Gravitational Search Algorithm (SKF-GSA)

Citation

Muhammad, Badaruddin and Ibrahim, Zuwairie and Mat Jusof, Mohd Falfazli and Ab. Aziz, Nor Azlina and Abdul Aziz, Nor Hidayati and Mokhtar, Norrima (2017) A Hybrid Simulated Kalman Filter - Gravitational Search Algorithm (SKF-GSA). 2017 International Conference on Artificial Life and Robotics (ICAROB 2017). pp. 707-710.

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Abstract

In this paper, simulated Kalman filter (SKF) and gravitational search algorithm (GSA) are hybridized in such a way that GSA is employed as prediction operator in SKF. The performance is compared using CEC2014 benchmark dataset. The proposed hybrid SKF-GSA shown to perform better than individual SKF and GSA algorithm.

Item Type: Article
Uncontrolled Keywords: Kalman filtering, hybrid, simulated Kalman filter, gravitational search algorithm, CEC2014 benchmark problem
Subjects: Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 26 Nov 2020 10:27
Last Modified: 26 Nov 2020 10:29
URII: http://shdl.mmu.edu.my/id/eprint/7114

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