{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T04:09:04Z","timestamp":1772770144156,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,12,6]],"date-time":"2022-12-06T00:00:00Z","timestamp":1670284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China National Railway Group Co., Ltd.","award":["K2021G027"],"award-info":[{"award-number":["K2021G027"]}]},{"name":"China National Railway Group Co., Ltd.","award":["XZ202101ZD0001G"],"award-info":[{"award-number":["XZ202101ZD0001G"]}]},{"name":"Science and Technology for the Sichuan-Tibet Railway Special Project","award":["K2021G027"],"award-info":[{"award-number":["K2021G027"]}]},{"name":"Science and Technology for the Sichuan-Tibet Railway Special Project","award":["XZ202101ZD0001G"],"award-info":[{"award-number":["XZ202101ZD0001G"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water inrush is one of the most important risk factors in tunnel construction because of its abruptness and timeliness. Various geophysical data used in actual construction contain useful information related to groundwater development. However, the existing approaches with such data from multiple sources and sensors are generally independent and cannot integrate this information, leading to inaccurate projections. In addition, existing tunnel advanced geological forecast reports for risk projections interpreted by human operators generally contain no quantitative observations or measurements, but only consist of ambiguous and uncertain qualitative descriptions. To surmount the problems above, this paper proposes a tunnel water inrush risk analysis method by fusing multi-source geophysical observations with fuzzy identification factors. Specifically, the membership function of the fuzzy set is used to solve the difficulty in determining the basic probability assignment function in the improved Dempster\u2013Shafer evidence theory. The prediction model of effluent conditions fuses seismic wave reflection data, ground penetrating radar data, and transient electromagnetic data. Therefore, quantitative evaluations of the effluent conditions are achieved, including the strand water, linear water, seepage and dripping water, and anhydrous. Experimental evaluations with a typical tunnel section were conducted, in which the state of the groundwater from a series of geological sketch reports in this sectionpaper were used as ground truth for verification. The experimental results revealed that the proposed method not only has high accuracy and robustness but also aligns well with different evidence effectively that generally contradicts manual interpretation reports. The results from 12 randomly selected tunnel sections also demonstrate the generalization abilities of the proposed method.<\/jats:p>","DOI":"10.3390\/rs14236178","type":"journal-article","created":{"date-parts":[[2022,12,7]],"date-time":"2022-12-07T04:00:37Z","timestamp":1670385637000},"page":"6178","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Improved Dempster\u2013Shafer Evidence Theory for Tunnel Water Inrush Risk Analysis Based on Fuzzy Identification Factors of Multi-Source Geophysical Data"],"prefix":"10.3390","volume":"14","author":[{"given":"Yulin","family":"Ding","sequence":"first","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"}]},{"given":"Binru","family":"Yang","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"}]},{"given":"Guangchun","family":"Xu","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"},{"name":"Innovation Center of Geological Survey Institute, China Railway Design Corporation, Tianjin 610081, China"}]},{"given":"Xiaoyong","family":"Wang","sequence":"additional","affiliation":[{"name":"China Railway 14TH Bureau Group Corporation Limited, Jinan 250014, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,6]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Challenges and technological breakthroughs in tunnel construction in China","volume":"33","author":"Chen","year":"2020","journal-title":"China J. 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