Twin support vector regression for characterizing uncertainty in surface reconstruction
Author:
Funder
Natural Science Foundation of Sichuan Province
Introduced Talent Research Start-up Funds of Chengdu Technological University
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-70109-y.pdf
Reference31 articles.
1. Hao, M. et al. 3d geological modeling and visualization of above-ground and underground integration-taking the unicorn island in Tianfu new area as an example. Earth Sci. Inform. 12, 465–474 (2019).
2. Li, J., Liu, P., Wang, X., Cui, H. & Ma, Y. 3d geological implicit modeling method of regular voxel splitting based on layered interpolation data. Sci. Rep. 12, 13840 (2022).
3. Liu, H. et al. Three-dimensional modeling of fault geological structure using generalized triangular prism element reconstruction. Bull. Eng. Geol. Environ. 82, 118 (2023).
4. Yu, S.-C., Lu, C. & Hu, G.-M. Reconstruction of geological surfaces using chance-constrained programming. Appl. Geophys. 16, 125–136 (2019).
5. Yang, L., Hyde, D., Grujic, O., Scheidt, C. & Caers, J. Assessing and visualizing uncertainty of 3d geological surfaces using level sets with stochastic motion. Comput. Geosci. 122, 54–67 (2019).
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