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In this paper, an enhanced fractional-order grey model is proposed based on a new fractional-order accumulated generating operator. The newly introduced model estimates parameters by utilizing the method of least squares and determines the order of the model through the implementation of metaheuristic algorithms. Our results show that, after conducting both Monte Carlo simulations and practical case analyses, the newly proposed model outperforms both existing grey prediction models and machine learning models in small sample environments, thus demonstrating superior forecast accuracy. Moreover, our experiments reveal that the proposed model has a simpler structure than previously developed grey models and achieves greater prediction accuracy.<\/jats:p>","DOI":"10.3233\/jifs-230121","type":"journal-article","created":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T10:07:58Z","timestamp":1692698878000},"page":"7575-7586","source":"Crossref","is-referenced-by-count":1,"title":["A novel fractional Hausdorff grey system model and its applications"],"prefix":"10.1177","volume":"45","author":[{"given":"Wanli","family":"Xie","sequence":"first","affiliation":[{"name":"School of Communication, Qufu Normal University, Rizhao, China"}]},{"given":"Zhenguo","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Communication, Qufu Normal University, Rizhao, China"}]},{"given":"Caixia","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Intelligent Education, Jiangsu Normal University, Xuzhou, 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