A Diversity-Based Adaptive Synchronous-Asynchronous Switching Simulated Kalman Filter Optimizer


Ab Aziz, Nor Azlina and Abdul Aziz, Nor Hidayati and Muhammad, Badaruddin and Ibrahim, Zuwairie and Mubin, Marizan and Mokhtar, Norrima and Mohamad, Mohd Saberi (2020) A Diversity-Based Adaptive Synchronous-Asynchronous Switching Simulated Kalman Filter Optimizer. In: InECCE2019. Lecture Notes in Electrical Engineering, 632 . Springer Nature, pp. 113-126. ISBN 978-981-15-2316-8, 978-981-15-2317-5

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The original Simulated Kalman Filter (SKF) is an optimizer that employs synchronous update mechanism. The agents in SKF update their solutions after all fitness calculations, prediction process, and measurement process are completed. An alternative to synchronous update is asynchronous update. In asynchronous update, only one agent does fitness calculation, prediction, measurement, and estimation processes at one time. Recent study found that the original SKF is subjected to premature convergence. Thus, synchronous and asynchronous mechanisms are combined in SKF to address the premature convergence problem in SKF. At first, the SKF starts with synchronous update. If no improved solution is found, the SKF changes its update mechanism. The decision to switch from synchronous to asynchronous or vice versa is made based on the information of the population. In this paper, population’s diversity is used as switching indicator. Using the CEC2014 benchmark test suite, experimental results indicate that the proposed diversity-based adaptive switching synchronous-asynchronous SKF outperforms the original SKF significantly.

Item Type: Book Section
Uncontrolled Keywords: Kalman filtering, Simulated kalman filter, Synchronous, Asynchronous
Subjects: Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 08 Dec 2020 20:32
Last Modified: 21 Dec 2022 06:17
URII: http://shdl.mmu.edu.my/id/eprint/7804


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