Parameter Tuning in the Single-Solution Simulated Kalman Filter Optimizer

Citation

Abdul Aziz, Nor Hidayati and Ibrahim, Zuwairie and Ab Aziz, Nor Azlina and Muhammad, Badaruddin and Ab Rahman, Tasiransurini and Mohamad, Mohd Saberi and Rahmad, Suhazri Amrin (2020) Parameter Tuning in the Single-Solution Simulated Kalman Filter Optimizer. In: Intelligent Manufacturing and Mechatronics. Lecture Notes in Mechanical Engineering . Springer, pp. 48-56.

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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.

Item Type: Book Section
Uncontrolled Keywords: Kalman filtering, Optimization, Simulated Kalman filter
Subjects: Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 16 Dec 2020 13:13
Last Modified: 16 Dec 2020 13:13
URII: http://shdl.mmu.edu.my/id/eprint/7966

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