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Volume 56 Issue 5
Oct.  2021
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Journal of Southwest Jiaotong University  > 2021  >  56(5): 1020-1028.
YU Jiang, TAO Hongqun, WANG Yating, WANG Yizheng, PENG Weidong, RAN Zongxin, HE Yulong. Influence of Phosphorus Control on Coupling System ofWinery Wastewater and Microalgae Cultivation[J]. Journal of Southwest Jiaotong University, 2019, 54(3): 655-662. doi: 10.3969/j.issn.0258-2724.20180585
Citation: WANG Feng, LIU Bofeng, CHAI Shuying, WANG Danlu. Urbanization Attribute Evaluation for Prefabricated Substation Based on MCD-AHP[J]. Journal of Southwest Jiaotong University, 2021, 56(5): 1020-1028. doi: 10.3969/j.issn.0258-2724.20200172
shu

Urbanization Attribute Evaluation for Prefabricated Substation Based on MCD-AHP

doi: 10.3969/j.issn.0258-2724.20200172
  • Received Date: 10 Apr 2020
  • Rev Recd Date: 20 Jul 2020
    • Available Online: 16 Sep 2020
  • Publish Date: 15 Oct 2021
    Abstract
  • In order to improve the urbanization attribute effect of the prefabricated substation construction for urban rail transits, it is necessary to make an accurate evaluation of its urbanization attribute index. First, an evaluation system of prefabricated substation urbanization attribute indexes is built, including economic attributes, social attributes, and energy-saving attributes, and a quantitative model of the evaluation indexes is presented. Then, the robust analysis method with the minimum covariance determinant (MCD) is used to detect the judgment matrix provided by the expert group in the analytic hierarchy process (AHP) and remove the outlier matrix due to the difference in subjective cognition among the members of the expert group. Finally, the improved MCD-AHP is used to calculate and evaluate the weights of the urbanization attribute indexes for the prefabricated substation. The results show that after removing the outlier matrix samples, the absolute value of the index weight difference calculated by the upper and lower limit matrices ranges from 0 to 0.0103, and the the relative change ratio is from 0 to 9.31%, which is significantly better than the corresponding ranges of 0.0138−0.1355 and 15.99%−106.23% under the full sample state. This method can effectively improve the logical consistency of the judgment matrix and the aggregation of weight values.

     

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