Abstract Based on the optical properties of symmetric structures independent of each other in the orthogonal direction, an all-dielectric nano-square hole array metasurface which is symmetric along the diagonal is proposed. By changing the size of square nanopores, the symmetry of the periodic unit structure is broken and the double Fano resonance can be excited. The influence of each structural parameter on the sensing performance of the metasurface is analyzed respectively. As the main structural parameters and performance index, the metasurface height and the lengths of the main and sub-diagonal square nanoholes are selected as the input parameters, and the figure of merit (FOM) value is used as the output value. Then the nonlinear mapping relationship between the input and the output is established through deep extreme learning machine (DELM). Different optimization algorithms are used to optimize the weighted FOM values globally. The four evaluation indicators including root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and model fit (R-squared, R2) are used to assess the training effectiveness of the model. It is shown that the indexes are 0.9986, 0.9725, 3.1612 and 0.9733 respectively, and the FOM values of the dual Fano resonance after pelican optimization algorithm ( POA ) optimization are as high as 9.88 × 103 and 1.28 × 105, which demonstrate the effectiveness of POA-DELM proposed in this paper.