A weight optimization method for chemical safety evaluation indicators based on the bipartite graph and random walk

被引：2

作者：

Du, Junwei ^{[1
]}

Jing, Guanghui ^{[1
]}

Hu, Qiang ^{[1
]}

机构：

[1] Qingdao Univ Sci & Technol, Coll Informat Sci & Technol, Qingdao 266061, Peoples R China

来源：

JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING | 2022年 / 9卷 / 04期

关键词：

weight optimization; chemical safety; bipartite graph; random walk; EVALUATION INDEX SYSTEM; GROUP DECISION-MAKING; RISK-ASSESSMENT; FUZZY-AHP; CONSTRUCTION; ALGORITHM;

D O I：

10.1093/jcde/qwac050

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In the chemical safety evaluation system, the optimization of indicator weights needs to take both experts' evaluations and the feedback on accident influences into account. Thus, this paper proposes a comprehensive weighting method based on the association bipartite graph (ABG). The accident influences and correlation intensity between the accident and the evaluation indicators are calculated on the ABG. A random walk algorithm, which integrates the objective influences of the accidents and the subjective evaluations of experts, is designed to realize the weight optimization. Experiments prove the effectiveness of the proposed method from the perspectives of weight ranking and fitting degree.

引用

页码：1214 / 1217

页数：4

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