[1] Pasciak J E. The mathematical theory of finite element methods (Susanne C. Brenner and L. Ridgway Scott)[J]. SIAM Rev, 37, 472-473(1995).

[2] Salminen T, Lehtinen K E J, Seppänen A. Application of the finite element method to the multicomponent general dynamic equation of aerosols[J]. J Aerosol Sci, 174, 106260(2023).

[3] Barth T, Ohlberger M, Stein E, de Borst R, Hughes T J R. Finite volume methods: foundation and analysis[M]. Encyclopedia of Computational Mechanics, 1-60(2004). https://doi.org/10.1002/0470091355.ecm010

[4] Berger M J, Oliger J. Adaptive mesh refinement for hyperbolic partial differential equations[J]. J Comput Phys, 53, 484-512(1984).

[5] Perera R, Agrawal V. Dynamic and adaptive mesh-based graph neural network framework for simulating displacement and crack fields in phase field models[J]. Mech Mater, 186, 104789(2023).

[6] Zhao Y X, Li H R, Zhou H S et al. A review of graph neural network applications in mechanics-related domains[J]. Artif Intell Rev, 57, 315(2024).

[7] Economon T D, Palacios F, Copeland S R et al. SU2: an open-source suite for multiphysics simulation and design[J]. AIAA J, 54, 828-846(2016).

[8] Marburg S, Nolte B[M]. Computational Acoustics of Noise Propagation in Fluids-Finite and Boundary Element Methods(2008). https://doi.org/10.1007/978-3-540-77448-8

[9] Verfürth R. A posteriori error estimation and adaptive mesh-refinement techniques[J]. J Comput Appl Math, 50, 67-83(1994).

[10] Xie L J, Chen J J, Liang Y et al. Geometry-based adaptive mesh generation for continuous and discrete parametric surfaces[J]. J Inf Comput Sci, 9, 2327-2344(2012).

[11] Möller M, Kuzmin D. Adaptive mesh refinement for high‐resolution finite element schemes[J]. Int J Numer Methods Fluids, 52, 545-569(2006).

[12] Triantafyllidis D G, Labridis D P. A finite-element mesh generator based on growing neural networks[J]. IEEE Trans Neural Netw, 13, 1482-1496(2002).

[13] Jilani H, Bahreininejad A, Ahmadi M T. Adaptive finite element mesh triangulation using self-organizing neural networks[J]. Adv Eng Softw, 40, 1097-1103(2009).

[14] Bohn J, Feischl M. Recurrent neural networks as optimal mesh refinement strategies[J]. Comput Math Appl, 97, 61-76(2021).

[15] Zhang Z Y, Wang Y X, Jimack P K et al. MeshingNet: a new mesh generation method based on deep learning[C], 186-198(2020). https://doi.org/10.1007/978-3-030-50420-5_14

[16] Wu Z H, Pan S R, Chen F W et al. A comprehensive survey on graph neural networks[J]. IEEE Trans Neural Netw Learn Syst, 32, 4-24(2020).

[17] Zhang L Y, Sun H H, Sun Y F et al. Review of node classification methods based on graph convolutional neural networks[J]. Comput Sci, 51, 95-105(2024).

[18] Kim M, Lee J, Kim J. GMR-Net: GCN-based mesh refinement framework for elliptic PDE problems[J]. Eng Comput, 39, 3721-3737(2023).

[19] Khan A, Yamada M, Chikane A et al. GraphMesh: geometrically generalized mesh refinement using GNNs[C], 120-134(2024). https://doi.org/10.1007/978-3-031-63775-9_9

[20] Pelissier U, Parret-Fréaud A, Bordeu F et al. Graph neural networks for mesh generation and adaptation in structural and fluid mechanics[J]. Mathematics, 12, 2933(2024).

[21] Peng J M, Chen X H, Liu J. 3DMeshNet: a three-dimensional differential neural network for structured mesh generation[J]. Graph Models, 139, 101257(2025).

[22] Rowbottom J, Maierhofer G, Deveney T et al. G-adaptivity: optimised graph-based mesh relocation for finite element methods[Z](2024).

[23] Freymuth N, Dahlinger P, Würth T et al. Swarm reinforcement learning for adaptive mesh refinement[C], 3206(2024).

[24] Liang L M, Dong X, Li R J et al. Classification algorithm of retinopathy based on attention mechanism and multi feature fusion[J]. Opto-Electron Eng, 50, 220199(2023).

[25] Zhang H M, Tian Q Q, Yan D D et al. GLCrowd: a weakly supervised global-local attention model for congested crowd counting[J]. Opto-Electron Eng, 51, 240174(2024).

[26] Scarselli F, Gori M, Tsoi A C et al. The graph neural network model[J]. IEEE Trans Neural Netw, 20, 61-80(2009).

[27] Shang Y M, Wu A B, Yuan Y et al. Graph neural network enhancement based on personalized PageRank high-order neighborhood aggregation[J]. Comput Eng(2024).

[28] Brody S, Alon U, Yahav E. How attentive are graph attention networks?[C], 1-26(2022).

[29] Yun S, Jeong M, Kim R et al. Graph transformer networks[C], 1073(2019).

[30] Geuzaine C, Remacle J F. Gmsh: a 3‐D finite element mesh generator with built‐in pre‐and post‐processing facilities[J]. Int J Numer Methods Eng, 79, 1309-1331(2009).

[31] Gustafsson T, Mcbain G D. scikit-fem: a Python package for finite element assembly[J]. J Open Source Softw, 5, 2369(2020).