Recent years saw tremendous developments of data-driven modeling in various engineering fields. As for the contact modeling between complex surfaces, the utilization of neural networks successfully eliminates the limitations encountered by the traditional physics-based contact modeling strategy. However, contrary to its increasingly extensive applications, very little attention has been paid to the role of network hyper-parameters in reducing the model redundancy and improving its training efficiency. In this work, a novel neural network considering link switches has been presented for the dat...
