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Optimisation of Engineering Systems With the Bees Algorithm
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Author(s): Duc T. Pham (University of Birmingham, Birmingham, UK), Luca Baronti (University of Birmingham, Birmingham, UK), Biao Zhang (Harbin Institute of Technology, Harbin, China)and Marco Castellani (University of Birmingham, Birmingham, UK)
Copyright: 2018
Volume: 8
Issue: 1
Pages: 15
Source title:
International Journal of Artificial Life Research (IJALR)
Editor(s)-in-Chief: Maki K. Habib (The American University in Cairo, Egypt)
DOI: 10.4018/IJALR.2018010101
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Abstract
This article describes the Bees Algorithm in standard formulation and presents two applications to real-world continuous optimisation engineering problems. In the first case, the Bees Algorithm is employed to train three artificial neural networks (ANNs) to model the inverse kinematics of the joints of a three-link manipulator. In the second case, the Bees Algorithm is used to optimise the parameters of a linear model used to approximate the torque output for an electro-hydraulic load system. In both cases, the Bees Algorithm outperformed the state-of-the-art in the literature, proving to be an effective optimisation technique for engineering systems.
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