Novel adaptive bacterial foraging algorithms for global optimisation with application to modelling of a TRS

Author:

Nasir A.N.K.,Tokhi M.O.,Ghani N.M.A.

Funder

Ministry of Higher Education, Malaysia

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference32 articles.

1. Synergy of PSO and bacterial foraging optimization – a comparative study on numerical benchmarks;Biswas,2007

2. Chen, Y., & Lin, W. (2009). An improved bacterial foraging optimization. In Proceeding of IEEE international conference on robotics and biomimetics, ROBIO2019, Guilin, Guangxi, China, 19–23 Dec. 2009 (pp. 2057–2062).

3. Representations of non-linear systems: The NARMAX model;Chen;International Journal of Control,1989

4. Chu, Y., Mi, H., Liao, H., Ji, Z., & Wu, Q. H. (2008). A fast bacterial swarming algorithm for high-dimensional function optimization. In Proceeding of 2008 IEEE congress on evolutionary computation (CEC 2008), 1–6 June 2008, Hong Kong (pp. 3135–3140).

5. Chemo-inspired genetic algorithm for function optimization;Das;Applied Mathematics and Computation,2013

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