[1] [1] SAFIABADI TALI S H, HAJIMIRI H, SADIQ Z, et al. Engineered detection zone to enhance color uniformity on paper microfluidics fabricatedvia Parafilm®-heating-laser-cutting［J］. Sensors and Actuators B: Chemical, 2023, 380: 133324.

[4] [4] HUANG S F, FU Z D, LIU C, et al. Interactional relations between ablation and heat affected zone (HAZ) in laser cutting of glass fiber reinforced polymer (GFRP) composite by fiber laser［J］. Optics & Laser Technology, 2023, 158: 108796.

[6] [6] SINGH Y, SINGH J, SHARMA S, et al. Process parameter optimization in laser cutting of Coir fiber reinforced Epoxy composite： A review［J］. Materials Today: Proceedings, 2022, 48: 1021-1027.

[8] [8] BAKHTIYARI A N, WANG Z W, WANG L Y, et al. A review on applications of artificial intelligence in modeling and optimization of laser beam machining［J］. Optics & Laser Technology, 2021, 135: 106721.

[9] [9] KECHAGIAS J D, TSIOLIKAS A, PETOUSIS M, et al. A robust methodology for optimizing the topology and the learning parameters of an ANN for accurate predictions of laser-cut edges surface roughness［J］. Simulation Modelling Practice and Theory, 2022, 114: 102414.

[10] [10] LI M, YU J, YIN Z, et al. Research on technological innovation opportunities based on patent analysis and technological evolution［C］//2021 2nd International Conference on Intelligent Design (ICID). ［s.l.］：IEEE, 2021: 466-471.

[32] [32] TATZEL L, LEN F P. Image-based roughness estimation of laser cut edges with a convolutional neural network［J］. Procedia CIRP, 2020, 94: 469-473.

[33] [33] GARCA A T, LEVICHEV N, VORKOV V, et al. Roughness prediction of laser cut edges by image processing and artificial neural networks［J］. Procedia Manufacturing, 2021, 54: 257-262.

[34] [34] SIBALIJA T, PETRONIC S, MILOVANOVIC D. Experimental optimization ofnimonic 263 laser cutting using a particle swarm approach［J］. Metals, 2019, 9(11): 1147.

[35] [35] ZHANG Y L, LEI J H. Prediction of laser cutting roughness in intelligent manufacturing mode based on ANFIS［J］. Procedia Engineering, 2017, 174: 82-89.