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The potential problems of the backpropagation (BP) neural network with slothful speed of convergence and the possibility of falling into the local minimum point are solved to a convinced degree using the genetic algorithm in combination. The hybrid technique of the genetic BP neural network is applied to a credit rating system. Using commercial banks\u2019 datasets, our experimental evaluations suggest that, using a combination of the BP neural network and the genetic algorithm, the proposed model has high accuracy in enterprise credit rating and has good application value. Moreover, the proposed model is approximately 15.9% more accurate than the classical BP neural network approach.<\/jats:p>","DOI":"10.1155\/2021\/7745920","type":"journal-article","created":{"date-parts":[[2021,9,2]],"date-time":"2021-09-02T22:20:09Z","timestamp":1630621209000},"page":"1-8","source":"Crossref","is-referenced-by-count":9,"title":["Research on Credit Evaluation of Financial Enterprises Based on the Genetic Backpropagation Neural Network"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6850-2603","authenticated-orcid":true,"given":"Hua","family":"Peng","sequence":"first","affiliation":[{"name":"Wuyi University, Wuyishan 354300, China"},{"name":"National Changhua University of Education, Changhua 50007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","article-title":"Enterprise credit rating model based on BP neural networks","volume":"2","author":"H. 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