{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T13:50:15Z","timestamp":1769694615784,"version":"3.49.0"},"reference-count":27,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T00:00:00Z","timestamp":1632096000000},"content-version":"vor","delay-in-days":262,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010754","name":"Zhejiang Gongshang University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010754","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>With the development of science and technology, system management is gradually applied to tourism management. How to correctly assess the security risks of the tourism management system has become an important means to maintain passenger information. The security risk index of the travel management system is input into the PSO\u2010BP network as a sample, and the corresponding risk value of the index is used as the network output. The results show that the error results, accuracy (96.53%), training time (216\u2009s), number of iterations (275 times), and convergence speed are all better than traditional BP network. The relative error of PSO\u2010BP network (0.32%) is better than that of BP network, with 300 iterations, and the error is close to 10\u20135. The average evaluation accuracy of <jats:italic>S<\/jats:italic> based on PSO\u2010BP network is 99.72%, and the average time consumed is 2.512\u2009s. It is superior to the evaluation model based on fuzzy set and entropy weight theory and the evaluation model based on gray correlation analysis and radial basis function neural network. In conclusion, the security risk assessment of the tourism management system based on PSO\u2010BP network can effectively assess the security risk of the tourism management system.<\/jats:p>","DOI":"10.1155\/2021\/1980037","type":"journal-article","created":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T23:20:30Z","timestamp":1632180030000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["[Retracted] Safety Risk Assessment of Tourism Management System Based on PSO\u2010BP Neural 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