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Susceptibility evaluation based on connection cloud model and improved conflict evidence fusion method for debris flow disaster
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Guangyao CHEN1, Sihao LI1, Yangze LIANG1, Zhenzhao XIA2, Zhao XU1, **
China Safety Science Journal | 2024, 34(8) : 222 - 230
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China Safety Science Journal | 2024, 34(8): 222-230
Technology and engineering of disaster prevention and mitigation
Susceptibility evaluation based on connection cloud model and improved conflict evidence fusion method for debris flow disaster
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Guangyao CHEN1, Sihao LI1, Yangze LIANG1, Zhenzhao XIA2, Zhao XU1, **
Affiliations
  • 1 School of Civil Engineering,Southeast University,Nanjing Jiangsu 211189,China
  • 2 School of Civil and Hydraulic Engineering,Huazhong University of Science and Technology,Wuhan Hubei 430074,China
Published: 2024-08-28 doi: 10.16265/j.cnki.issn1003-3033.2024.08.1882
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Debris flow,as a common geological disaster,has a complex formation mechanism with numerous influencing factors and multiple uncertainties. To comprehensively consider the synergistic effects of various influencing factors,based on information fusion and uncertainty analysis theory,this paper proposed a debris flow susceptibility evaluation method based on evidence theory and cloud model. Firstly,the BPA function of key evaluation indicators for debris flow susceptibility was calculated using a connection cloud model. Subsequently,the reliability and uncertainty of the indicators' BPA were modified using Lance distance and DENG entropy,respectively,resulting in a corrected BPA. Finally,evidence fusion was performed on the corrected BPA based on Dempster-Shafer (D-S) evidence theory to achieve debris flow susceptibility assessment,followed by a case validation. The results show that the connection cloud model used in this paper overcomes the limitation that the normal cloud model requires indicators to follow the normal distribution when calculating BPA,and it considers the randomness and uncertainty of indicator distribution. The proposed method's evaluation results are generally consistent with those of four other commonly used evidence fusion methods,proving it to be effective and feasible for debris flow susceptibility evaluation. The conflict evidence fusion method improved based on Lance distance and DENG entropy can enhance the convergence speed and precision of evidence fusion,making the results more accurate and reliable.

connection cloud model(CCM)  /  debris flow  /  susceptibility evaluation  /  basic probability assignment (BPA)  /  conflict evidence fusion  /  Lance distance  /  DENG entropy  /  evidence fusion
Guangyao CHEN, Sihao LI, Yangze LIANG, Zhenzhao XIA, Zhao XU. Susceptibility evaluation based on connection cloud model and improved conflict evidence fusion method for debris flow disaster[J]. China Safety Science Journal, 2024 , 34 (8) : 222 -230 . DOI: 10.16265/j.cnki.issn1003-3033.2024.08.1882
Year 2024 volume 34 Issue 8
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doi: 10.16265/j.cnki.issn1003-3033.2024.08.1882
  • Receive Date:2024-02-21
  • Online Date:2025-07-09
  • Published:2024-08-28
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  • Received:2024-02-21
  • Revised:2024-05-27
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    1 School of Civil Engineering,Southeast University,Nanjing Jiangsu 211189,China
    2 School of Civil and Hydraulic Engineering,Huazhong University of Science and Technology,Wuhan Hubei 430074,China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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