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This paper aims to use fuzzy logic algorithms to process financial data, improve data mining efficiency, explore new information disclosure methods, and design an information disclosure evaluation model based on fuzzy logic algorithms. The experiment constructed a financial data mining model based on an adaptive neural fuzzy inference system (ANFIS), optimized the model parameters using a fuzzy genetic algorithm (FGA), and used a fuzzy comprehensive evaluation model to form information disclosure content with the help of logical reasoning. The research results show that the model accuracy of financial data mining reaches 96.38%, which has a good effect on information disclosure, and the algorithm efficiency is better than that of traditional algorithms.<\/jats:p>","DOI":"10.1177\/14727978251321954","type":"journal-article","created":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T14:19:31Z","timestamp":1741097971000},"page":"591-604","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Financial data mining and information disclosure supported by fuzzy logic algorithms"],"prefix":"10.1177","volume":"25","author":[{"given":"Yonghui","family":"Liu","sequence":"first","affiliation":[{"name":"Longdong University"}]},{"given":"Zhenhua","family":"Wang","sequence":"additional","affiliation":[{"name":"Longdong University"}]}],"member":"179","published-online":{"date-parts":[[2025,3,4]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Ravula S. 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