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The Realization and Application of AI Reconstruction Method of Stratum Information Based on FCN
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Weijian Feng1, Yong Lu1, Linlin Gu2, Yupeng Cao3, Cunxin Fan1
Chinese Journal of Underground Space and Engineering | 2026, 22(2) : 653 - 663
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Chinese Journal of Underground Space and Engineering | 2026, 22(2): 653-663
The Realization and Application of AI Reconstruction Method of Stratum Information Based on FCN
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Weijian Feng1, Yong Lu1, Linlin Gu2, Yupeng Cao3, Cunxin Fan1
Affiliations
  • 1.School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu 215011, P. R China
  • 2.Department of Civil Engineering, Nanjing University of Science and Technology, Nanjing 210094, P. R. China
  • 3.The Department of Urban Management, Department of Urban Management, National Kyoto University of Japan, Kyoto 606-8511, Japan
Published: 2026-04-20 doi: 10.20174/j.JUSE.2026.02.27
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It is quite important for the refined design and construction of geotechnical engineering to obtain a certain amount of borehole data and then determine the stratum profile information through geotechnical investigation. However, due to the particularity of the area where some engineering sites are located (existing old urban areas, cultural Relic Protection Building, etc.), there is often a problem that the borehole data is difficult to obtain, which makes the corresponding stratum information determination challenging. To this end, an artificial intelligence (AI) method for stratum information reconstruction is developed based on the fully convolutional network (FCN). The core idea of this method is to use the existing borehole data in the region as a learning sample, analyze and extract the multi-dimensional information features of the sample (vertical stratification, horizontal extension), and then use this information feature as a template to perform probability-based stratum profile information interpolation reconstruction for engineering sites with only a small amount of borehole data. Through the study and reconstruction of the geological survey data of a tunnel project and foundation pit project in the ancient city of Suzhou, it is found that the accuracy of stratum prediction gradually tends to be stable after the number of simulations increases to more than 30 times, and can reach about 90%. This verifies the applicability of the developed AI reconstruction method of stratum information, which will provide an effective choice for the prediction of complex stratum information in related projects.

geotechnical investigation  /  stratum profile information  /  fully convolutional network  /  artificial intelligence
Weijian Feng, Yong Lu, Linlin Gu, Yupeng Cao, Cunxin Fan. The Realization and Application of AI Reconstruction Method of Stratum Information Based on FCN[J]. Chinese Journal of Underground Space and Engineering, 2026 , 22 (2) : 653 -663 . DOI: 10.20174/j.JUSE.2026.02.27
Year 2026 volume 22 Issue 2
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doi: 10.20174/j.JUSE.2026.02.27
  • Receive Date:2025-06-18
  • Online Date:2026-06-17
  • Published:2026-04-20
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  • Received:2025-06-18
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Affiliations
    1.School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu 215011, P. R China
    2.Department of Civil Engineering, Nanjing University of Science and Technology, Nanjing 210094, P. R. China
    3.The Department of Urban Management, Department of Urban Management, National Kyoto University of Japan, Kyoto 606-8511, Japan
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表12种不同金属材料的力学参数

Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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