Comprehensive evaluation method based on entropy theory and intermediate truth value measurement

Xiaodan Cai; XiangXiang Mei; XiaoJing Jiang; Xiangxin Xie; Ying Tang

doi:10.1117/12.2683179

26 June 2023 Comprehensive evaluation method based on entropy theory and intermediate truth value measurement

Xiaodan Cai, XiangXiang Mei, XiaoJing Jiang, Xiangxin Xie, Ying Tang

Proceedings Volume 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023); 127141G (2023) https://doi.org/10.1117/12.2683179
Event: Third International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 2023, Sanya, China

Abstract

Comprehensive evaluation problems can be seen everywhere in life, and there are many comprehensive evaluation methods. Among them, the intermediate truth value measurement method based on fuzzy mathematics is one of the methods to evaluate multi-index objects. It is a method that can effectively deal with fuzzy phenomena, and it is also a subjective weighting method. In order to make the evaluation results more objective, this paper proposes a comprehensive evaluation method based on the combination of entropy theory and intermediate truth measure, which applies the entropy theory to the acquisition of the first-level index weight, and it uses the analytic hierarchy process based on expert scoring to calculate the second-level index weight. This method effectively reduces the error caused by the completely subjective calculation of the weight value in the intermediary truth measurement method. Finally, the method is applied to the quality assessment of residential projects. Compared with the measure of truth scale and the entropy weight method, the proposed method in this paper is more feasible and effective.

Citation Download Citation

Xiaodan Cai, XiangXiang Mei, XiaoJing Jiang, Xiangxin Xie, and Ying Tang "Comprehensive evaluation method based on entropy theory and intermediate truth value measurement", Proc. SPIE 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 127141G (26 June 2023); https://doi.org/10.1117/12.2683179

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