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Classical sequential three-way decisions are based on a granular structure with a single threshold under multiple levels of granularity, which make the traditional models incapable of adapting to the case of multiview granular structures with multiple thresholds. To overcome this disadvantage, Qian et\u00a0al. proposed a generalized multigranulation sequential three-way decision model based on multiple different thresholds. We have observed that multiple different thresholds will determine the same positive and negative regions in sequential three-way decision model. That is, there exists a many-to-one relationship between parameter thresholds and positive\/negative regions. Therefore, it is essential to investigate parameter threshold selection strategies. First, since parameter thresholds taken from the same interval may result in identical positive and negative regions for single-granularity sequential three-way decision model based on multiple different thresholds. Therefore, some effective strategies of determining the selection interval of thresholds are put forward, which can greatly reduce the repeated operations and improve the decision efficiency. Second, the parameter selection strategy in the single-granularity sequential three-way decision model proposed in this paper is extended to the multi-granularity sequential three-way decision model, which can further improve decision-making efficiency.<\/jats:p>","DOI":"10.1142\/s0218194025500895","type":"journal-article","created":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T09:44:36Z","timestamp":1761212676000},"page":"781-802","source":"Crossref","is-referenced-by-count":0,"title":["Threshold Selection Strategy for Sequential Three-Way Decision Model"],"prefix":"10.1142","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5300-7378","authenticated-orcid":false,"given":"Qinrong","family":"Feng","sequence":"first","affiliation":[{"name":"School of Computer Science and Artificial Intelligence, Shanxi Normal University, Taiyuan 030031, Shanxi Province, P. R. 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