Abstract
The paper deals with an application of the artificial immune system (AIS) and particle swarm optimizer (PSO) to the identification problem of piezoelectric structures analyzed by the boundary element method (BEM). The AIS and PSO is applied to identify material properties of piezoelectrics. The AIS is a computational adaptive system inspired by the principles, processes and mechanisms of biological immune systems. The algorithms typically use the characteristics of the immune systems like learning and memory to simulate and solve a problem in a computational manner. The PSO algorithm is based on the models of the animals social behaviours: moving and living in the groups. PSO algorithm realizes directed motion of the particles in n-dimensional space to search for solution for n-variable optimisation problem.The main advantage of the bioinspired methods (AIS and PSO), contrary to gradient methods of optimization, is the fact that it does not need any information about the gradient of fitness function.
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Poteralski, A., Szczepanik, M., Dziatkiewicz, G., Kuś, W., Burczyński, T. (2013). Comparison between PSO and AIS on the Basis of Identification of Material Constants in Piezoelectrics. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7895. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38610-7_52
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DOI: https://doi.org/10.1007/978-3-642-38610-7_52
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