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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.<\/jats:p>","DOI":"10.1093\/jcde\/qwac050","type":"journal-article","created":{"date-parts":[[2022,6,8]],"date-time":"2022-06-08T17:30:45Z","timestamp":1654709445000},"page":"1214-1229","source":"Crossref","is-referenced-by-count":0,"title":["A weight optimization method for chemical safety evaluation indicators based on the bipartite graph and random walk"],"prefix":"10.1093","volume":"9","author":[{"given":"Junwei","family":"Du","sequence":"first","affiliation":[{"name":"College of Information Science and Technology, Qingdao University of Science and Technology , Qingdao 266061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanghui","family":"Jing","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Qingdao University of Science and Technology , Qingdao 266061, 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