<p>Resonant ultrasound spectroscopy (RUS), a nondestructive testing technology based on free resonance frequencies, can be employed to derive all anisotropic elastic constants in one test. In the inverse framework, the iterative algorithm is applied to constantly update elastic parameters in the calculation model to minimize the relative error between calculated and observed resonance frequencies. The process has a significant impact on the elastic identification efficiency. In this paper, existing inverse algorithms are evaluated by fitting error, iteration time and uncertainty in results to provide a basis for algorithm investigation. For rapid testing demands, the algorithm, in which fuzzy logic is introduced to adaptively modify the parameter in particle swarm optimization (PSO), is devised to solve the inverse issue. It has been proven to have the lowest final fitting error and superior repeatability independent of initial guesses. The calculation time is reduced by 15% and 52.9% for TC4 and human cortical bone compared with PSO, respectively. Furthermore, it still attains the best convergence performance for human cortical bone with one-third of measured resonance frequencies missing due to high material loss. The proposed inverse approach aims to accomplish rapid determination of low-symmetry elastic constants with imperfect measurement information.</p>