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 |
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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: | 21 Dec 2022 06:14 |
URII: | http://shdl.mmu.edu.my/id/eprint/7114 |
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