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Parameter Tuning in the Single-Solution Simulated Kalman Filter Optimizer

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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.

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References

  1. Ibrahim, Z., Abdul Aziz, N.H., Ab Aziz, N.A., Razali, S., Shapiai, M.I.: A Kalman filter approach for solving unimodal optimization problem. ICIC Express Lett. 9, 3415–3422 (2015)

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  2. Ibrahim, Z., Abdul Aziz, N.H., Ab Aziz, N.A., Razali, S., Mohamad, M.S.: Simulated Kalman filter: a novel estimation-based metaheuristic optimization algorithm. Adv. Sci. Lett. 22, 2941–2946 (2016)

    Article  Google Scholar 

  3. Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.: Single-solution simulated Kalman filter algorithm for global optimisation problems. Sadhana 43 (2018)

    Google Scholar 

  4. Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Yusof, Z.M., Mohamad, M.S.: Single-solution simulated Kalman filter algorithm for routing in printed circuit board drilling process. Lecture Notes in Mechanical Engineering (Intelligent Manufacturing & Mechatronics), pp. 649–655 (2018)

    Google Scholar 

  5. Liang, J.J., Qu, B.Y., Suganthan, P.N.: Problem definitions and evaluation criteria for the CEC 2014 special session and competition on single objective real-parameter numerical optimization. Technical report 201311, Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou, China and Nanyang Technological University, Singapore (2013)

    Google Scholar 

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Acknowledgments

This research is supported by the Fundamental Research Grant Scheme awarded by the Ministry of Higher Education Malaysia to Universiti Malaysia Pahang (RDU170106).

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Correspondence to Zuwairie Ibrahim .

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Abdul Aziz, N.H. et al. (2020). Parameter Tuning in the Single-Solution Simulated Kalman Filter Optimizer. In: Jamaludin, Z., Ali Mokhtar, M.N. (eds) Intelligent Manufacturing and Mechatronics. SympoSIMM 2019. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-9539-0_5

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  • DOI: https://doi.org/10.1007/978-981-13-9539-0_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9538-3

  • Online ISBN: 978-981-13-9539-0

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