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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2016  >  16(4): 112-121
WANG Shuang-jie, XIONG Li, ZHANG Chi, MU Ke, JIN Long. Fuzzy expert prediction method for highway diseases in permafrost region[J]. Journal of Traffic and Transportation Engineering, 2016, 16(4): 112-121. doi: 10.19818/j.cnki.1671-1637.2016.04.012
Citation: WANG Shuang-jie, XIONG Li, ZHANG Chi, MU Ke, JIN Long. Fuzzy expert prediction method for highway diseases in permafrost region[J]. Journal of Traffic and Transportation Engineering, 2016, 16(4): 112-121. doi: 10.19818/j.cnki.1671-1637.2016.04.012
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Fuzzy expert prediction method for highway diseases in permafrost region

doi: 10.19818/j.cnki.1671-1637.2016.04.012
  • 1.

    State Key Laboratory of Road Engineering Safety and Health in Cold and High-Altitude Regions, CCCC First Highway Consultants Co., Ltd., Xi'an 710075, Shaanxi, China

  • 2.

    Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang'an University, Xi'an 710064, Shaanxi, China

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  • Author Bio:

    WANG Shuang-jie(1962-), male, senior engineer, PhD, +86-29-88320807, wangshj@ccroad.com.cn

  • Received Date: 2016-06-21
  • Publish Date: 2016-08-25
    Abstract
  • To predict the disease sections of newly-built highway in permafrost region and assist the decision-makers to carry on the reasonable design at design stage, a highway disease prediction method in permafrost region was proposed based on fuzzy expert system. The disease degree was used as analysis index, a road section of the Qinghai-Tibet Highway was selected as research object, and the influence factors of road disease were qualitative analyzed. The disease degrees of Qinghai-Tibet Highway were divided into 3levels according to actual disease data. Combined with the years of disease data of annual average ground temperature, ice content and frozen-heave factor of Qinghai-Tibet Highway, the fuzzy expert system for identifying disease sections in permafrost region was built. A variety of influence factors were used as input variables, and the disease degrees of the 10 equidistance road sections in permafrost region were calculated by using the Fuzzy Logic Toolbox of MATLAB. The calculated disease degree and the actual disease degree were compared and analyzed by using SPSS software. Analysis result showsthat the road disease degree increases with the increase of annual average ground temperature, ice content and frozen-heave factor, the relevance between the calculated disease degree and the actual disease degree is 0.751, so, the application of fuzzy expert system in the prediction of highway diseases in permafrost region has a beneficial effect.

     

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