Abstract
Metaheursitc algorithms are used to solve hard optimization problems which can not be solved using traditional approaches within reasonable time and using feasible resources. One of the new natural inspired metaheursitc algorithms is the Cuckoo Search (CS) which is stimulated by the brood parasitism of some Cuckoo species. In this research, we explore the application of CS to solve the problem of parameter estimation of a nonlinear manufacturing process model. An industrial metal cutting system is used to examine the effectiveness of the proposed approach and also to compare CS with other metaheuristic approaches like genetic algorithm and particle swarm optimization. Results shows the high efficiency and robustness of CS when applied to the problem of parameter estimation of a nonlinear system model.
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Aly, W.M., Sheta, A. (2013). Parameter Estimation of Nonlinear Systems Using Lèvy Flight Cuckoo Search. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXX. SGAI 2013. Springer, Cham. https://doi.org/10.1007/978-3-319-02621-3_33
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DOI: https://doi.org/10.1007/978-3-319-02621-3_33
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