Application of Biologically Inspired Algorithms for Determining the Coefficients of Empirical Models for Determining Sound Absorption

Abstract

The paper investigates the possibility of applying biologically inspired algorithms for determining the optimal values of the coefficients in known empirical models for acoustic impedance. To solve this problem, a gray wolf algorithm was used, for cases of infinite and deterministic search space. Using the gray wolf algorithm, new values of the coefficients in the empirical model for the impedance of foam materials were determined. The new model provides satisfactory predictions of the sound absorption coefficient of open-cell polyurethane foams, compared to the experimental results obtained in an impedance tube. Known empirical models for impedance in which the constants are determined by the method of linear regression, give slightly better predictions of the coefficient of sound absorption of polyurethane foams compared to the new model in which the constants are determined using the gray wolf algorithm. The presented method of determining the coefficients of empirical models for impedance provides a basis for the application of other biologically oriented algorithms, as well as for their hybridization