Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/392
Title: Parameter tuning in the single-solution simulated Kalman filter optimizer
Authors: Abdul Aziz N.H. 
Ibrahim Z. 
Ab Aziz N.A. 
Muhammad B. 
Ab Rahman T. 
Mohamad, MS 
Rahmad S.A. 
Keywords: Optimization;Simulated Kalman filter
Issue Date: 2020
Publisher: Springer Nature Singapore Pte Ltd.
Journal: Lecture Notes in Mechanical Engineering 
Conference: 2nd Symposium on Intelligent Manufacturing and Mechatronics, SympoSIMM 2019 
Abstract: 
Single-solution simulated Kalman filter (ssSKF) is a variant of simulated Kalman filter (SKF) algorithm. Both algorithms employ the well-known Kalman filtering mechanism in an optimization process. Unlike the population-based SKF, the ssSKF operates using one agent. In this paper, parameter tuning of the ssSKF algorithm is presented.
Description: 
Scopus
URI: http://hdl.handle.net/123456789/392
ISSN: 21954356
DOI: 10.1007/978-981-13-9539-0_5
Appears in Collections:Faculty of Bioengineering and Technology - Proceedings

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