Abstract
Data detailed on Machine Learning have been presented. According to news originating from Hefei, People's Republic of China, by NewsRx correspondents, research stated, "In the realm of numerical sim ulations concerning vehicle mobility, the establishment of a high-fidelity soil discrete element model often necessitates substantial parameter adjustments to a lign with the mechanical responses of actual soil. In pursuit of a rapid and pre cise calibration of the microparameters of the soil model, this paper describes an approach rooted in machine learning surrogate models." Funders for this research include Youth Innovation Promotion Association of the CAS, Dreams Foundation of Jianghuai Advance Technology Center, Hefei Key Common Technology Research and Development, "Unveiling and Leading" Project.
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