A Fitness-Based Adaptive Synchronous-Asynchronous Switching in Simulated Kalman Filter Optimizer


Ab Aziz, Nor Azlina and Abdul Aziz, Nor Hidayati and Ibrahim, Zuwairie and Mubin, Marizan and Mokhtar, Norrima and Shapiai, Mohd Ibrahim (2019) A Fitness-Based Adaptive Synchronous-Asynchronous Switching in Simulated Kalman Filter Optimizer. In: 2019 International Conference on Computer and Information Sciences, ICCIS 2019, 3-4 April 2019, Sakaka, Saudi Arabia.

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Simulated Kalman Filter (SKF) is a population-based optimizer introduced in 2015 that is based on Kalman filtering, which consists of prediction, measurement, and estimation processes. The original SKF algorithm employs synchronous update mechanism in which 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. In this study, synchronous and asynchronous mechanisms are combined in SKF. At first, the SKF starts with synchronous update. If no improved solution is found, the SKF changes its update mechanism. Using the CEC2014 benchmark test suite, experimental results indicate that the proposed adaptive switching synchronous-asynchronous SKF outperforms the original SKF significantly.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Asynchronous
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 07 Jan 2022 03:13
Last Modified: 21 Dec 2022 06:22
URII: http://shdl.mmu.edu.my/id/eprint/8953


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