A fitness-based adaptive synchronous-asynchronous switching in simulated kalman filter optimizer

Nor Azlina, Ab. Aziz and Marizan, Mubin and Zuwairie, Ibrahim and Norrima, Mokhtar and Nor Hidayati, Abdul Aziz and Mohd Ibrahim, Shapiai (2019) A fitness-based adaptive synchronous-asynchronous switching in simulated kalman filter optimizer. In: International Conference on Computer and Information Sciences, ICCIS 2019 , 3 - 4 April 2019 , Jouf University, Aljouf, Kingdom of Saudi Arabia. pp. 1-5.. ISBN 978-153868125-1

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Abstract

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 (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Asynchronous; Optimization; Synchronous; Simulated kalman filter
Subjects: T Technology > TS Manufactures
Faculty/Division: Faculty of Manufacturing Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 24 Oct 2019 03:49
Last Modified: 24 Oct 2019 03:49
URI: http://umpir.ump.edu.my/id/eprint/24944
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