Figure6

Suspension parameter identification method for rail transit vehicles using an AO-GRBF surrogate model and non-dominated sorting genetic algorithm

Figure 6. Comparison of vertical vibration acceleration before and after parameter identification by various methods. (A) Comparison with GRBF; (B) Comparison with RBFNN; (C) Comparison with RBF-HDMR; (D) Comparison with LSTM; (E) Comparison with Transformer. All subfigures show the measured data (black) and the unidentified baseline (black dashed) as references. The proposed method (red) and other approaches show different levels of consistency with experimental observations. GRBF: Gaussian radial basis function; RBFNN: radial basis function neural network; RBF-HDMR: radial basis function high-dimensional model representation; LSTM: long short-term memory.

Intelligence & Robotics
ISSN 2770-3541 (Online)

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/