Identification of structural parameters based on symbolic time series analysis and differential evolution strategy

Abstract

A novel symbolization strategy, dynamic strategy, of symbolization state series analysis (STSA) is employed in symbolization-based differential evolution strategy (SDES) to alleviate the effects of harmful noise. Procedure of dynamic strategy is described, effect of parameters in dynamic is verified, cases of partial output are considered. Performance of the proposed methodology was numerically compared with other symbolization strategies. Particle swarm optimization (PSO) and differential evolution (DE) on raw acceleration data are used as comparison to show the good noise immunity of our proposed methodology. These simulations revealed that our proposed methodology is a powerful tool for identifying the unknown parameters of structural systems even when the data is contaminated with relatively large amounts of noise.